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  <h1>News</h1>

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        var(--jp-shadow-base-lightness),
        0.12
    );
    --jp-elevation-z0: none;
    --jp-elevation-z1: 0px 2px 1px -1px var(--jp-shadow-umbra-color),
        0px 1px 1px 0px var(--jp-shadow-penumbra-color),
        0px 1px 3px 0px var(--jp-shadow-ambient-color);
    --jp-elevation-z2: 0px 3px 1px -2px var(--jp-shadow-umbra-color),
        0px 2px 2px 0px var(--jp-shadow-penumbra-color),
        0px 1px 5px 0px var(--jp-shadow-ambient-color);
    --jp-elevation-z4: 0px 2px 4px -1px var(--jp-shadow-umbra-color),
        0px 4px 5px 0px var(--jp-shadow-penumbra-color),
        0px 1px 10px 0px var(--jp-shadow-ambient-color);
    --jp-elevation-z6: 0px 3px 5px -1px var(--jp-shadow-umbra-color),
        0px 6px 10px 0px var(--jp-shadow-penumbra-color),
        0px 1px 18px 0px var(--jp-shadow-ambient-color);
    --jp-elevation-z8: 0px 5px 5px -3px var(--jp-shadow-umbra-color),
        0px 8px 10px 1px var(--jp-shadow-penumbra-color),
        0px 3px 14px 2px var(--jp-shadow-ambient-color);
    --jp-elevation-z12: 0px 7px 8px -4px var(--jp-shadow-umbra-color),
        0px 12px 17px 2px var(--jp-shadow-penumbra-color),
        0px 5px 22px 4px var(--jp-shadow-ambient-color);
    --jp-elevation-z16: 0px 8px 10px -5px var(--jp-shadow-umbra-color),
        0px 16px 24px 2px var(--jp-shadow-penumbra-color),
        0px 6px 30px 5px var(--jp-shadow-ambient-color);
    --jp-elevation-z20: 0px 10px 13px -6px var(--jp-shadow-umbra-color),
        0px 20px 31px 3px var(--jp-shadow-penumbra-color),
        0px 8px 38px 7px var(--jp-shadow-ambient-color);
    --jp-elevation-z24: 0px 11px 15px -7px var(--jp-shadow-umbra-color),
        0px 24px 38px 3px var(--jp-shadow-penumbra-color),
        0px 9px 46px 8px var(--jp-shadow-ambient-color);

    /* Borders
   *
   * The following variables, specify the visual styling of borders in JupyterLab.
   */

    --jp-border-width: 1px;
    --jp-border-color0: var(--md-grey-400);
    --jp-border-color1: var(--md-grey-400);
    --jp-border-color2: var(--md-grey-300);
    --jp-border-color3: var(--md-grey-200);
    --jp-border-radius: 2px;

    /* UI Fonts
   *
   * The UI font CSS variables are used for the typography all of the JupyterLab
   * user interface elements that are not directly user generated content.
   *
   * The font sizing here is done assuming that the body font size of --jp-ui-font-size1
   * is applied to a parent element. When children elements, such as headings, are sized
   * in em all things will be computed relative to that body size.
   */

    --jp-ui-font-scale-factor: 1.2;
    --jp-ui-font-size0: 0.83333em;
    --jp-ui-font-size1: 13px; /* Base font size */
    --jp-ui-font-size2: 1.2em;
    --jp-ui-font-size3: 1.44em;

    --jp-ui-font-family: -apple-system, BlinkMacSystemFont, "Segoe UI",
        Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji",
        "Segoe UI Symbol";

    /*
   * Use these font colors against the corresponding main layout colors.
   * In a light theme, these go from dark to light.
   */

    /* Defaults use Material Design specification */
    --jp-ui-font-color0: rgba(0, 0, 0, 1);
    --jp-ui-font-color1: rgba(0, 0, 0, 0.87);
    --jp-ui-font-color2: rgba(0, 0, 0, 0.54);
    --jp-ui-font-color3: rgba(0, 0, 0, 0.38);

    /*
   * Use these against the brand/accent/warn/error colors.
   * These will typically go from light to darker, in both a dark and light theme.
   */

    --jp-ui-inverse-font-color0: rgba(255, 255, 255, 1);
    --jp-ui-inverse-font-color1: rgba(255, 255, 255, 1);
    --jp-ui-inverse-font-color2: rgba(255, 255, 255, 0.7);
    --jp-ui-inverse-font-color3: rgba(255, 255, 255, 0.5);

    /* Content Fonts
   *
   * Content font variables are used for typography of user generated content.
   *
   * The font sizing here is done assuming that the body font size of --jp-content-font-size1
   * is applied to a parent element. When children elements, such as headings, are sized
   * in em all things will be computed relative to that body size.
   */

    --jp-content-line-height: 1.6;
    --jp-content-font-scale-factor: 1.2;
    --jp-content-font-size0: 0.83333em;
    --jp-content-font-size1: 14px; /* Base font size */
    --jp-content-font-size2: 1.2em;
    --jp-content-font-size3: 1.44em;
    --jp-content-font-size4: 1.728em;
    --jp-content-font-size5: 2.0736em;

    /* This gives a magnification of about 125% in presentation mode over normal. */
    --jp-content-presentation-font-size1: 17px;

    --jp-content-heading-line-height: 1;
    --jp-content-heading-margin-top: 1.2em;
    --jp-content-heading-margin-bottom: 0.8em;
    --jp-content-heading-font-weight: 500;

    /* Defaults use Material Design specification */
    --jp-content-font-color0: rgba(0, 0, 0, 1);
    --jp-content-font-color1: rgba(0, 0, 0, 0.87);
    --jp-content-font-color2: rgba(0, 0, 0, 0.54);
    --jp-content-font-color3: rgba(0, 0, 0, 0.38);

    --jp-content-link-color: var(--md-blue-700);

    --jp-content-font-family: -apple-system, BlinkMacSystemFont, "Segoe UI",
        Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji",
        "Segoe UI Symbol";

    /*
   * Code Fonts
   *
   * Code font variables are used for typography of code and other monospaces content.
   */

    --jp-code-font-size: 13px;
    --jp-code-line-height: 1.3077; /* 17px for 13px base */
    --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */
    --jp-code-font-family-default: Menlo, Consolas, "DejaVu Sans Mono",
        monospace;
    --jp-code-font-family: var(--jp-code-font-family-default);

    /* This gives a magnification of about 125% in presentation mode over normal. */
    --jp-code-presentation-font-size: 16px;

    /* may need to tweak cursor width if you change font size */
    --jp-code-cursor-width0: 1.4px;
    --jp-code-cursor-width1: 2px;
    --jp-code-cursor-width2: 4px;

    /* Layout
   *
   * The following are the main layout colors use in JupyterLab. In a light
   * theme these would go from light to dark.
   */

    --jp-layout-color0: white;
    --jp-layout-color1: white;
    --jp-layout-color2: var(--md-grey-200);
    --jp-layout-color3: var(--md-grey-400);
    --jp-layout-color4: var(--md-grey-600);

    /* Inverse Layout
   *
   * The following are the inverse layout colors use in JupyterLab. In a light
   * theme these would go from dark to light.
   */

    --jp-inverse-layout-color0: #111111;
    --jp-inverse-layout-color1: var(--md-grey-900);
    --jp-inverse-layout-color2: var(--md-grey-800);
    --jp-inverse-layout-color3: var(--md-grey-700);
    --jp-inverse-layout-color4: var(--md-grey-600);

    /* Brand/accent */

    --jp-brand-color0: var(--md-blue-900);
    --jp-brand-color1: var(--md-blue-700);
    --jp-brand-color2: var(--md-blue-300);
    --jp-brand-color3: var(--md-blue-100);
    --jp-brand-color4: var(--md-blue-50);

    --jp-accent-color0: var(--md-green-900);
    --jp-accent-color1: var(--md-green-700);
    --jp-accent-color2: var(--md-green-300);
    --jp-accent-color3: var(--md-green-100);

    /* State colors (warn, error, success, info) */

    --jp-warn-color0: var(--md-orange-900);
    --jp-warn-color1: var(--md-orange-700);
    --jp-warn-color2: var(--md-orange-300);
    --jp-warn-color3: var(--md-orange-100);

    --jp-error-color0: var(--md-red-900);
    --jp-error-color1: var(--md-red-700);
    --jp-error-color2: var(--md-red-300);
    --jp-error-color3: var(--md-red-100);

    --jp-success-color0: var(--md-green-900);
    --jp-success-color1: var(--md-green-700);
    --jp-success-color2: var(--md-green-300);
    --jp-success-color3: var(--md-green-100);

    --jp-info-color0: var(--md-cyan-900);
    --jp-info-color1: var(--md-cyan-700);
    --jp-info-color2: var(--md-cyan-300);
    --jp-info-color3: var(--md-cyan-100);

    /* Cell specific styles */

    --jp-cell-padding: 5px;

    --jp-cell-collapser-width: 8px;
    --jp-cell-collapser-min-height: 20px;
    --jp-cell-collapser-not-active-hover-opacity: 0.6;

    --jp-cell-editor-background: var(--md-grey-100);
    --jp-cell-editor-border-color: var(--md-grey-300);
    --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300);
    --jp-cell-editor-active-background: var(--jp-layout-color0);
    --jp-cell-editor-active-border-color: var(--jp-brand-color1);

    --jp-cell-prompt-width: 64px;
    --jp-cell-prompt-font-family: var(--jp-code-font-family-default);
    --jp-cell-prompt-letter-spacing: 0px;
    --jp-cell-prompt-opacity: 1;
    --jp-cell-prompt-not-active-opacity: 0.5;
    --jp-cell-prompt-not-active-font-color: var(--md-grey-700);
    /* A custom blend of MD grey and blue 600
   * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */
    --jp-cell-inprompt-font-color: #307fc1;
    /* A custom blend of MD grey and orange 600
   * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */
    --jp-cell-outprompt-font-color: #bf5b3d;

    /* Notebook specific styles */

    --jp-notebook-padding: 10px;
    --jp-notebook-select-background: var(--jp-layout-color1);
    --jp-notebook-multiselected-color: var(--md-blue-50);

    /* The scroll padding is calculated to fill enough space at the bottom of the
  notebook to show one single-line cell (with appropriate padding) at the top
  when the notebook is scrolled all the way to the bottom. We also subtract one
  pixel so that no scrollbar appears if we have just one single-line cell in the
  notebook. This padding is to enable a 'scroll past end' feature in a notebook.
  */
    --jp-notebook-scroll-padding: calc(
        100% - var(--jp-code-font-size) * var(--jp-code-line-height) -
            var(--jp-code-padding) - var(--jp-cell-padding) - 1px
    );

    /* Rendermime styles */

    --jp-rendermime-error-background: #fdd;
    --jp-rendermime-table-row-background: var(--md-grey-100);
    --jp-rendermime-table-row-hover-background: var(--md-light-blue-50);

    /* Dialog specific styles */

    --jp-dialog-background: rgba(0, 0, 0, 0.25);

    /* Console specific styles */

    --jp-console-padding: 10px;

    /* Toolbar specific styles */

    --jp-toolbar-border-color: var(--jp-border-color1);
    --jp-toolbar-micro-height: 8px;
    --jp-toolbar-background: var(--jp-layout-color1);
    --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.24);
    --jp-toolbar-header-margin: 4px 4px 0px 4px;
    --jp-toolbar-active-background: var(--md-grey-300);

    /* Statusbar specific styles */

    --jp-statusbar-height: 24px;

    /* Input field styles */

    --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300);
    --jp-input-active-background: var(--jp-layout-color1);
    --jp-input-hover-background: var(--jp-layout-color1);
    --jp-input-background: var(--md-grey-100);
    --jp-input-border-color: var(--jp-border-color1);
    --jp-input-active-border-color: var(--jp-brand-color1);
    --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3);

    /* General editor styles */

    --jp-editor-selected-background: #d9d9d9;
    --jp-editor-selected-focused-background: #d7d4f0;
    --jp-editor-cursor-color: var(--jp-ui-font-color0);

    /* Code mirror specific styles */

    --jp-mirror-editor-keyword-color: #008000;
    --jp-mirror-editor-atom-color: #88f;
    --jp-mirror-editor-number-color: #080;
    --jp-mirror-editor-def-color: #00f;
    --jp-mirror-editor-variable-color: var(--md-grey-900);
    --jp-mirror-editor-variable-2-color: #05a;
    --jp-mirror-editor-variable-3-color: #085;
    --jp-mirror-editor-punctuation-color: #05a;
    --jp-mirror-editor-property-color: #05a;
    --jp-mirror-editor-operator-color: #aa22ff;
    --jp-mirror-editor-comment-color: #408080;
    --jp-mirror-editor-string-color: #ba2121;
    --jp-mirror-editor-string-2-color: #708;
    --jp-mirror-editor-meta-color: #aa22ff;
    --jp-mirror-editor-qualifier-color: #555;
    --jp-mirror-editor-builtin-color: #008000;
    --jp-mirror-editor-bracket-color: #997;
    --jp-mirror-editor-tag-color: #170;
    --jp-mirror-editor-attribute-color: #00c;
    --jp-mirror-editor-header-color: blue;
    --jp-mirror-editor-quote-color: #090;
    --jp-mirror-editor-link-color: #00c;
    --jp-mirror-editor-error-color: #f00;
    --jp-mirror-editor-hr-color: #999;

    /* Vega extension styles */

    --jp-vega-background: white;

    /* Sidebar-related styles */

    --jp-sidebar-min-width: 250px;

    /* Search-related styles */

    --jp-search-toggle-off-opacity: 0.5;
    --jp-search-toggle-hover-opacity: 0.8;
    --jp-search-toggle-on-opacity: 1;
    --jp-search-selected-match-background-color: rgb(245, 200, 0);
    --jp-search-selected-match-color: black;
    --jp-search-unselected-match-background-color: var(
        --jp-inverse-layout-color0
    );
    --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0);

    /* Icon colors that work well with light or dark backgrounds */
    --jp-icon-contrast-color0: var(--md-purple-600);
    --jp-icon-contrast-color1: var(--md-green-600);
    --jp-icon-contrast-color2: var(--md-pink-600);
    --jp-icon-contrast-color3: var(--md-blue-600);
}

[data-md-color-scheme="slate"] .jupyter-wrapper {
    /* Elevation
   *
   * We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here:
   *
   * https://github.com/material-components/material-components-web
   * https://material-components-web.appspot.com/elevation.html
   */

    /* The dark theme shadows need a bit of work, but this will probably also require work on the core layout
   * colors used in the theme as well. */
    --jp-shadow-base-lightness: 32;
    --jp-shadow-umbra-color: rgba(
        var(--jp-shadow-base-lightness),
        var(--jp-shadow-base-lightness),
        var(--jp-shadow-base-lightness),
        0.2
    );
    --jp-shadow-penumbra-color: rgba(
        var(--jp-shadow-base-lightness),
        var(--jp-shadow-base-lightness),
        var(--jp-shadow-base-lightness),
        0.14
    );
    --jp-shadow-ambient-color: rgba(
        var(--jp-shadow-base-lightness),
        var(--jp-shadow-base-lightness),
        var(--jp-shadow-base-lightness),
        0.12
    );
    --jp-elevation-z0: none;
    --jp-elevation-z1: 0px 2px 1px -1px var(--jp-shadow-umbra-color),
        0px 1px 1px 0px var(--jp-shadow-penumbra-color),
        0px 1px 3px 0px var(--jp-shadow-ambient-color);
    --jp-elevation-z2: 0px 3px 1px -2px var(--jp-shadow-umbra-color),
        0px 2px 2px 0px var(--jp-shadow-penumbra-color),
        0px 1px 5px 0px var(--jp-shadow-ambient-color);
    --jp-elevation-z4: 0px 2px 4px -1px var(--jp-shadow-umbra-color),
        0px 4px 5px 0px var(--jp-shadow-penumbra-color),
        0px 1px 10px 0px var(--jp-shadow-ambient-color);
    --jp-elevation-z6: 0px 3px 5px -1px var(--jp-shadow-umbra-color),
        0px 6px 10px 0px var(--jp-shadow-penumbra-color),
        0px 1px 18px 0px var(--jp-shadow-ambient-color);
    --jp-elevation-z8: 0px 5px 5px -3px var(--jp-shadow-umbra-color),
        0px 8px 10px 1px var(--jp-shadow-penumbra-color),
        0px 3px 14px 2px var(--jp-shadow-ambient-color);
    --jp-elevation-z12: 0px 7px 8px -4px var(--jp-shadow-umbra-color),
        0px 12px 17px 2px var(--jp-shadow-penumbra-color),
        0px 5px 22px 4px var(--jp-shadow-ambient-color);
    --jp-elevation-z16: 0px 8px 10px -5px var(--jp-shadow-umbra-color),
        0px 16px 24px 2px var(--jp-shadow-penumbra-color),
        0px 6px 30px 5px var(--jp-shadow-ambient-color);
    --jp-elevation-z20: 0px 10px 13px -6px var(--jp-shadow-umbra-color),
        0px 20px 31px 3px var(--jp-shadow-penumbra-color),
        0px 8px 38px 7px var(--jp-shadow-ambient-color);
    --jp-elevation-z24: 0px 11px 15px -7px var(--jp-shadow-umbra-color),
        0px 24px 38px 3px var(--jp-shadow-penumbra-color),
        0px 9px 46px 8px var(--jp-shadow-ambient-color);

    /* Borders
   *
   * The following variables, specify the visual styling of borders in JupyterLab.
   */

    --jp-border-width: 1px;
    --jp-border-color0: var(--md-grey-700);
    --jp-border-color1: var(--md-grey-700);
    --jp-border-color2: var(--md-grey-800);
    --jp-border-color3: var(--md-grey-900);
    --jp-border-radius: 2px;

    /* UI Fonts
   *
   * The UI font CSS variables are used for the typography all of the JupyterLab
   * user interface elements that are not directly user generated content.
   *
   * The font sizing here is done assuming that the body font size of --jp-ui-font-size1
   * is applied to a parent element. When children elements, such as headings, are sized
   * in em all things will be computed relative to that body size.
   */

    --jp-ui-font-scale-factor: 1.2;
    --jp-ui-font-size0: 0.83333em;
    --jp-ui-font-size1: 13px; /* Base font size */
    --jp-ui-font-size2: 1.2em;
    --jp-ui-font-size3: 1.44em;

    --jp-ui-font-family: -apple-system, BlinkMacSystemFont, "Segoe UI",
        Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji",
        "Segoe UI Symbol";

    /*
   * Use these font colors against the corresponding main layout colors.
   * In a light theme, these go from dark to light.
   */

    /* Defaults use Material Design specification */
    --jp-ui-font-color0: rgba(255, 255, 255, 1);
    --jp-ui-font-color1: rgba(255, 255, 255, 0.87);
    --jp-ui-font-color2: rgba(255, 255, 255, 0.54);
    --jp-ui-font-color3: rgba(255, 255, 255, 0.38);

    /*
   * Use these against the brand/accent/warn/error colors.
   * These will typically go from light to darker, in both a dark and light theme.
   */

    --jp-ui-inverse-font-color0: rgba(0, 0, 0, 1);
    --jp-ui-inverse-font-color1: rgba(0, 0, 0, 0.8);
    --jp-ui-inverse-font-color2: rgba(0, 0, 0, 0.5);
    --jp-ui-inverse-font-color3: rgba(0, 0, 0, 0.3);

    /* Content Fonts
   *
   * Content font variables are used for typography of user generated content.
   *
   * The font sizing here is done assuming that the body font size of --jp-content-font-size1
   * is applied to a parent element. When children elements, such as headings, are sized
   * in em all things will be computed relative to that body size.
   */

    --jp-content-line-height: 1.6;
    --jp-content-font-scale-factor: 1.2;
    --jp-content-font-size0: 0.83333em;
    --jp-content-font-size1: 14px; /* Base font size */
    --jp-content-font-size2: 1.2em;
    --jp-content-font-size3: 1.44em;
    --jp-content-font-size4: 1.728em;
    --jp-content-font-size5: 2.0736em;

    /* This gives a magnification of about 125% in presentation mode over normal. */
    --jp-content-presentation-font-size1: 17px;

    --jp-content-heading-line-height: 1;
    --jp-content-heading-margin-top: 1.2em;
    --jp-content-heading-margin-bottom: 0.8em;
    --jp-content-heading-font-weight: 500;

    /* Defaults use Material Design specification */
    --jp-content-font-color0: rgba(255, 255, 255, 1);
    --jp-content-font-color1: rgba(255, 255, 255, 1);
    --jp-content-font-color2: rgba(255, 255, 255, 0.7);
    --jp-content-font-color3: rgba(255, 255, 255, 0.5);

    --jp-content-link-color: var(--md-blue-300);

    --jp-content-font-family: -apple-system, BlinkMacSystemFont, "Segoe UI",
        Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji",
        "Segoe UI Symbol";

    /*
   * Code Fonts
   *
   * Code font variables are used for typography of code and other monospaces content.
   */

    --jp-code-font-size: 13px;
    --jp-code-line-height: 1.3077; /* 17px for 13px base */
    --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */
    --jp-code-font-family-default: Menlo, Consolas, "DejaVu Sans Mono",
        monospace;
    --jp-code-font-family: var(--jp-code-font-family-default);

    /* This gives a magnification of about 125% in presentation mode over normal. */
    --jp-code-presentation-font-size: 16px;

    /* may need to tweak cursor width if you change font size */
    --jp-code-cursor-width0: 1.4px;
    --jp-code-cursor-width1: 2px;
    --jp-code-cursor-width2: 4px;

    /* Layout
   *
   * The following are the main layout colors use in JupyterLab. In a light
   * theme these would go from light to dark.
   */

    --jp-layout-color0: #111111;
    --jp-layout-color1: var(--md-grey-900);
    --jp-layout-color2: var(--md-grey-800);
    --jp-layout-color3: var(--md-grey-700);
    --jp-layout-color4: var(--md-grey-600);

    /* Inverse Layout
   *
   * The following are the inverse layout colors use in JupyterLab. In a light
   * theme these would go from dark to light.
   */

    --jp-inverse-layout-color0: white;
    --jp-inverse-layout-color1: white;
    --jp-inverse-layout-color2: var(--md-grey-200);
    --jp-inverse-layout-color3: var(--md-grey-400);
    --jp-inverse-layout-color4: var(--md-grey-600);

    /* Brand/accent */

    --jp-brand-color0: var(--md-blue-700);
    --jp-brand-color1: var(--md-blue-500);
    --jp-brand-color2: var(--md-blue-300);
    --jp-brand-color3: var(--md-blue-100);
    --jp-brand-color4: var(--md-blue-50);

    --jp-accent-color0: var(--md-green-700);
    --jp-accent-color1: var(--md-green-500);
    --jp-accent-color2: var(--md-green-300);
    --jp-accent-color3: var(--md-green-100);

    /* State colors (warn, error, success, info) */

    --jp-warn-color0: var(--md-orange-700);
    --jp-warn-color1: var(--md-orange-500);
    --jp-warn-color2: var(--md-orange-300);
    --jp-warn-color3: var(--md-orange-100);

    --jp-error-color0: var(--md-red-700);
    --jp-error-color1: var(--md-red-500);
    --jp-error-color2: var(--md-red-300);
    --jp-error-color3: var(--md-red-100);

    --jp-success-color0: var(--md-green-700);
    --jp-success-color1: var(--md-green-500);
    --jp-success-color2: var(--md-green-300);
    --jp-success-color3: var(--md-green-100);

    --jp-info-color0: var(--md-cyan-700);
    --jp-info-color1: var(--md-cyan-500);
    --jp-info-color2: var(--md-cyan-300);
    --jp-info-color3: var(--md-cyan-100);

    /* Cell specific styles */

    --jp-cell-padding: 5px;

    --jp-cell-collapser-width: 8px;
    --jp-cell-collapser-min-height: 20px;
    --jp-cell-collapser-not-active-hover-opacity: 0.6;

    --jp-cell-editor-background: var(--jp-layout-color1);
    --jp-cell-editor-border-color: var(--md-grey-700);
    --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300);
    --jp-cell-editor-active-background: var(--jp-layout-color0);
    --jp-cell-editor-active-border-color: var(--jp-brand-color1);

    --jp-cell-prompt-width: 64px;
    --jp-cell-prompt-font-family: var(--jp-code-font-family-default);
    --jp-cell-prompt-letter-spacing: 0px;
    --jp-cell-prompt-opacity: 1;
    --jp-cell-prompt-not-active-opacity: 1;
    --jp-cell-prompt-not-active-font-color: var(--md-grey-300);

    /* A custom blend of MD grey and blue 600
   * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */
    --jp-cell-inprompt-font-color: #307fc1;
    /* A custom blend of MD grey and orange 600
   * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */
    --jp-cell-outprompt-font-color: #bf5b3d;

    /* Notebook specific styles */

    --jp-notebook-padding: 10px;
    --jp-notebook-select-background: var(--jp-layout-color1);
    --jp-notebook-multiselected-color: rgba(33, 150, 243, 0.24);

    /* The scroll padding is calculated to fill enough space at the bottom of the
  notebook to show one single-line cell (with appropriate padding) at the top
  when the notebook is scrolled all the way to the bottom. We also subtract one
  pixel so that no scrollbar appears if we have just one single-line cell in the
  notebook. This padding is to enable a 'scroll past end' feature in a notebook.
  */
    --jp-notebook-scroll-padding: calc(
        100% - var(--jp-code-font-size) * var(--jp-code-line-height) -
            var(--jp-code-padding) - var(--jp-cell-padding) - 1px
    );

    /* Rendermime styles */

    --jp-rendermime-error-background: rgba(244, 67, 54, 0.28);
    --jp-rendermime-table-row-background: var(--md-grey-900);
    --jp-rendermime-table-row-hover-background: rgba(3, 169, 244, 0.2);

    /* Dialog specific styles */

    --jp-dialog-background: rgba(0, 0, 0, 0.6);

    /* Console specific styles */

    --jp-console-padding: 10px;

    /* Toolbar specific styles */

    --jp-toolbar-border-color: var(--jp-border-color2);
    --jp-toolbar-micro-height: 8px;
    --jp-toolbar-background: var(--jp-layout-color1);
    --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.8);
    --jp-toolbar-header-margin: 4px 4px 0px 4px;
    --jp-toolbar-active-background: var(--jp-layout-color0);

    /* Statusbar specific styles */

    --jp-statusbar-height: 24px;

    /* Input field styles */

    --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300);
    --jp-input-active-background: var(--jp-layout-color0);
    --jp-input-hover-background: var(--jp-layout-color2);
    --jp-input-background: var(--md-grey-800);
    --jp-input-border-color: var(--jp-border-color1);
    --jp-input-active-border-color: var(--jp-brand-color1);
    --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3);

    /* General editor styles */

    --jp-editor-selected-background: var(--jp-layout-color2);
    --jp-editor-selected-focused-background: rgba(33, 150, 243, 0.24);
    --jp-editor-cursor-color: var(--jp-ui-font-color0);

    /* Code mirror specific styles */

    --jp-mirror-editor-keyword-color: var(--md-green-500);
    --jp-mirror-editor-atom-color: var(--md-blue-300);
    --jp-mirror-editor-number-color: var(--md-green-400);
    --jp-mirror-editor-def-color: var(--md-blue-600);
    --jp-mirror-editor-variable-color: var(--md-grey-300);
    --jp-mirror-editor-variable-2-color: var(--md-blue-400);
    --jp-mirror-editor-variable-3-color: var(--md-green-600);
    --jp-mirror-editor-punctuation-color: var(--md-blue-400);
    --jp-mirror-editor-property-color: var(--md-blue-400);
    --jp-mirror-editor-operator-color: #aa22ff;
    --jp-mirror-editor-comment-color: #408080;
    --jp-mirror-editor-string-color: #ff7070;
    --jp-mirror-editor-string-2-color: var(--md-purple-300);
    --jp-mirror-editor-meta-color: #aa22ff;
    --jp-mirror-editor-qualifier-color: #555;
    --jp-mirror-editor-builtin-color: var(--md-green-600);
    --jp-mirror-editor-bracket-color: #997;
    --jp-mirror-editor-tag-color: var(--md-green-700);
    --jp-mirror-editor-attribute-color: var(--md-blue-700);
    --jp-mirror-editor-header-color: var(--md-blue-500);
    --jp-mirror-editor-quote-color: var(--md-green-300);
    --jp-mirror-editor-link-color: var(--md-blue-700);
    --jp-mirror-editor-error-color: #f00;
    --jp-mirror-editor-hr-color: #999;

    /* Vega extension styles */

    --jp-vega-background: var(--md-grey-400);

    /* Sidebar-related styles */

    --jp-sidebar-min-width: 250px;

    /* Search-related styles */

    --jp-search-toggle-off-opacity: 0.6;
    --jp-search-toggle-hover-opacity: 0.8;
    --jp-search-toggle-on-opacity: 1;
    --jp-search-selected-match-background-color: rgb(255, 225, 0);
    --jp-search-selected-match-color: black;
    --jp-search-unselected-match-background-color: var(
        --jp-inverse-layout-color0
    );
    --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0);

    /* scrollbar related styles. Supports every browser except Edge. */

    /* colors based on JetBrain's Darcula theme */

    --jp-scrollbar-background-color: #3f4244;
    --jp-scrollbar-thumb-color: 88, 96, 97; /* need to specify thumb color as an RGB triplet */

    --jp-scrollbar-endpad: 3px; /* the minimum gap between the thumb and the ends of a scrollbar */

    /* hacks for setting the thumb shape. These do nothing in Firefox */

    --jp-scrollbar-thumb-margin: 3.5px; /* the space in between the sides of the thumb and the track */
    --jp-scrollbar-thumb-radius: 9px; /* set to a large-ish value for rounded endcaps on the thumb */

    /* Icon colors that work well with light or dark backgrounds */
    --jp-icon-contrast-color0: var(--md-purple-600);
    --jp-icon-contrast-color1: var(--md-green-600);
    --jp-icon-contrast-color2: var(--md-pink-600);
    --jp-icon-contrast-color3: var(--md-blue-600);
}

:root{--md-red-50: #ffebee;--md-red-100: #ffcdd2;--md-red-200: #ef9a9a;--md-red-300: #e57373;--md-red-400: #ef5350;--md-red-500: #f44336;--md-red-600: #e53935;--md-red-700: #d32f2f;--md-red-800: #c62828;--md-red-900: #b71c1c;--md-red-A100: #ff8a80;--md-red-A200: #ff5252;--md-red-A400: #ff1744;--md-red-A700: #d50000;--md-pink-50: #fce4ec;--md-pink-100: #f8bbd0;--md-pink-200: #f48fb1;--md-pink-300: #f06292;--md-pink-400: #ec407a;--md-pink-500: #e91e63;--md-pink-600: #d81b60;--md-pink-700: #c2185b;--md-pink-800: #ad1457;--md-pink-900: #880e4f;--md-pink-A100: #ff80ab;--md-pink-A200: #ff4081;--md-pink-A400: #f50057;--md-pink-A700: #c51162;--md-purple-50: #f3e5f5;--md-purple-100: #e1bee7;--md-purple-200: #ce93d8;--md-purple-300: #ba68c8;--md-purple-400: #ab47bc;--md-purple-500: #9c27b0;--md-purple-600: #8e24aa;--md-purple-700: #7b1fa2;--md-purple-800: #6a1b9a;--md-purple-900: #4a148c;--md-purple-A100: #ea80fc;--md-purple-A200: #e040fb;--md-purple-A400: #d500f9;--md-purple-A700: #aa00ff;--md-deep-purple-50: #ede7f6;--md-deep-purple-100: #d1c4e9;--md-deep-purple-200: #b39ddb;--md-deep-purple-300: #9575cd;--md-deep-purple-400: #7e57c2;--md-deep-purple-500: #673ab7;--md-deep-purple-600: #5e35b1;--md-deep-purple-700: #512da8;--md-deep-purple-800: #4527a0;--md-deep-purple-900: #311b92;--md-deep-purple-A100: #b388ff;--md-deep-purple-A200: #7c4dff;--md-deep-purple-A400: #651fff;--md-deep-purple-A700: #6200ea;--md-indigo-50: #e8eaf6;--md-indigo-100: #c5cae9;--md-indigo-200: #9fa8da;--md-indigo-300: #7986cb;--md-indigo-400: #5c6bc0;--md-indigo-500: #3f51b5;--md-indigo-600: #3949ab;--md-indigo-700: #303f9f;--md-indigo-800: #283593;--md-indigo-900: #1a237e;--md-indigo-A100: #8c9eff;--md-indigo-A200: #536dfe;--md-indigo-A400: #3d5afe;--md-indigo-A700: #304ffe;--md-blue-50: #e3f2fd;--md-blue-100: #bbdefb;--md-blue-200: #90caf9;--md-blue-300: #64b5f6;--md-blue-400: #42a5f5;--md-blue-500: #2196f3;--md-blue-600: #1e88e5;--md-blue-700: #1976d2;--md-blue-800: #1565c0;--md-blue-900: #0d47a1;--md-blue-A100: #82b1ff;--md-blue-A200: #448aff;--md-blue-A400: #2979ff;--md-blue-A700: #2962ff;--md-light-blue-50: #e1f5fe;--md-light-blue-100: #b3e5fc;--md-light-blue-200: #81d4fa;--md-light-blue-300: #4fc3f7;--md-light-blue-400: #29b6f6;--md-light-blue-500: #03a9f4;--md-light-blue-600: #039be5;--md-light-blue-700: #0288d1;--md-light-blue-800: #0277bd;--md-light-blue-900: #01579b;--md-light-blue-A100: #80d8ff;--md-light-blue-A200: #40c4ff;--md-light-blue-A400: #00b0ff;--md-light-blue-A700: #0091ea;--md-cyan-50: #e0f7fa;--md-cyan-100: #b2ebf2;--md-cyan-200: #80deea;--md-cyan-300: #4dd0e1;--md-cyan-400: #26c6da;--md-cyan-500: #00bcd4;--md-cyan-600: #00acc1;--md-cyan-700: #0097a7;--md-cyan-800: #00838f;--md-cyan-900: #006064;--md-cyan-A100: #84ffff;--md-cyan-A200: #18ffff;--md-cyan-A400: #00e5ff;--md-cyan-A700: #00b8d4;--md-teal-50: #e0f2f1;--md-teal-100: #b2dfdb;--md-teal-200: #80cbc4;--md-teal-300: #4db6ac;--md-teal-400: #26a69a;--md-teal-500: #009688;--md-teal-600: #00897b;--md-teal-700: #00796b;--md-teal-800: #00695c;--md-teal-900: #004d40;--md-teal-A100: #a7ffeb;--md-teal-A200: #64ffda;--md-teal-A400: #1de9b6;--md-teal-A700: #00bfa5;--md-green-50: #e8f5e9;--md-green-100: #c8e6c9;--md-green-200: #a5d6a7;--md-green-300: #81c784;--md-green-400: #66bb6a;--md-green-500: #4caf50;--md-green-600: #43a047;--md-green-700: #388e3c;--md-green-800: #2e7d32;--md-green-900: #1b5e20;--md-green-A100: #b9f6ca;--md-green-A200: #69f0ae;--md-green-A400: #00e676;--md-green-A700: #00c853;--md-light-green-50: #f1f8e9;--md-light-green-100: #dcedc8;--md-light-green-200: #c5e1a5;--md-light-green-300: #aed581;--md-light-green-400: #9ccc65;--md-light-green-500: #8bc34a;--md-light-green-600: #7cb342;--md-light-green-700: #689f38;--md-light-green-800: #558b2f;--md-light-green-900: #33691e;--md-light-green-A100: #ccff90;--md-light-green-A200: #b2ff59;--md-light-green-A400: #76ff03;--md-light-green-A700: #64dd17;--md-lime-50: #f9fbe7;--md-lime-100: #f0f4c3;--md-lime-200: #e6ee9c;--md-lime-300: #dce775;--md-lime-400: #d4e157;--md-lime-500: #cddc39;--md-lime-600: #c0ca33;--md-lime-700: #afb42b;--md-lime-800: #9e9d24;--md-lime-900: #827717;--md-lime-A100: #f4ff81;--md-lime-A200: #eeff41;--md-lime-A400: #c6ff00;--md-lime-A700: #aeea00;--md-yellow-50: #fffde7;--md-yellow-100: #fff9c4;--md-yellow-200: #fff59d;--md-yellow-300: #fff176;--md-yellow-400: #ffee58;--md-yellow-500: #ffeb3b;--md-yellow-600: #fdd835;--md-yellow-700: #fbc02d;--md-yellow-800: #f9a825;--md-yellow-900: #f57f17;--md-yellow-A100: #ffff8d;--md-yellow-A200: #ffff00;--md-yellow-A400: #ffea00;--md-yellow-A700: #ffd600;--md-amber-50: #fff8e1;--md-amber-100: #ffecb3;--md-amber-200: #ffe082;--md-amber-300: #ffd54f;--md-amber-400: #ffca28;--md-amber-500: #ffc107;--md-amber-600: #ffb300;--md-amber-700: #ffa000;--md-amber-800: #ff8f00;--md-amber-900: #ff6f00;--md-amber-A100: #ffe57f;--md-amber-A200: #ffd740;--md-amber-A400: #ffc400;--md-amber-A700: #ffab00;--md-orange-50: #fff3e0;--md-orange-100: #ffe0b2;--md-orange-200: #ffcc80;--md-orange-300: #ffb74d;--md-orange-400: #ffa726;--md-orange-500: #ff9800;--md-orange-600: #fb8c00;--md-orange-700: #f57c00;--md-orange-800: #ef6c00;--md-orange-900: #e65100;--md-orange-A100: #ffd180;--md-orange-A200: #ffab40;--md-orange-A400: #ff9100;--md-orange-A700: #ff6d00;--md-deep-orange-50: #fbe9e7;--md-deep-orange-100: #ffccbc;--md-deep-orange-200: #ffab91;--md-deep-orange-300: #ff8a65;--md-deep-orange-400: #ff7043;--md-deep-orange-500: #ff5722;--md-deep-orange-600: #f4511e;--md-deep-orange-700: #e64a19;--md-deep-orange-800: #d84315;--md-deep-orange-900: #bf360c;--md-deep-orange-A100: #ff9e80;--md-deep-orange-A200: #ff6e40;--md-deep-orange-A400: #ff3d00;--md-deep-orange-A700: #dd2c00;--md-brown-50: #efebe9;--md-brown-100: #d7ccc8;--md-brown-200: #bcaaa4;--md-brown-300: #a1887f;--md-brown-400: #8d6e63;--md-brown-500: #795548;--md-brown-600: #6d4c41;--md-brown-700: #5d4037;--md-brown-800: #4e342e;--md-brown-900: #3e2723;--md-grey-50: #fafafa;--md-grey-100: #f5f5f5;--md-grey-200: #eeeeee;--md-grey-300: #e0e0e0;--md-grey-400: #bdbdbd;--md-grey-500: #9e9e9e;--md-grey-600: #757575;--md-grey-700: #616161;--md-grey-800: #424242;--md-grey-900: #212121;--md-blue-grey-50: #eceff1;--md-blue-grey-100: #cfd8dc;--md-blue-grey-200: #b0bec5;--md-blue-grey-300: #90a4ae;--md-blue-grey-400: #78909c;--md-blue-grey-500: #607d8b;--md-blue-grey-600: #546e7a;--md-blue-grey-700: #455a64;--md-blue-grey-800: #37474f;--md-blue-grey-900: #263238}.jupyter-wrapper{/*!

Copyright 2015-present Palantir Technologies, Inc. All rights reserved.
Licensed under the Apache License, Version 2.0.

*//*!

Copyright 2017-present Palantir Technologies, Inc. All rights reserved.
Licensed under the Apache License, Version 2.0.

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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="kn">import</span> <span class="nn">sys</span>
<span class="n">sys</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s2">&quot;../../FinNLP&quot;</span><span class="p">)</span>
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sys.path.append("../../FinNLP")</div>
        
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<h3 id="cnbs">CNBS<a class="anchor-link" href="#cnbs">&#182;</a></h3>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="kn">from</span> <span class="nn">finnlp.data_sources.news.cnbc_streaming</span> <span class="kn">import</span> <span class="n">CNBC_Streaming</span>
</pre></div>
<div id="cell-2" class="clipboard-copy-txt">from finnlp.data_sources.news.cnbc_streaming import CNBC_Streaming</div>
        
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">news_downloader</span> <span class="o">=</span> <span class="n">CNBC_Streaming</span><span class="p">()</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">download_streaming_search</span><span class="p">(</span><span class="n">keyword</span> <span class="o">=</span> <span class="s2">&quot;apple&quot;</span><span class="p">,</span> <span class="n">rounds</span> <span class="o">=</span> <span class="mi">3</span><span class="p">)</span>
</pre></div>
<div id="cell-3" class="clipboard-copy-txt">news_downloader = CNBC_Streaming()
news_downloader.download_streaming_search(keyword = "apple", rounds = 3)</div>
        
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<pre>Downloading ... 0 1 2 </pre>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">news_downloader</span><span class="o">.</span><span class="n">dataframe</span><span class="o">.</span><span class="n">shape</span>
</pre></div>
<div id="cell-4" class="clipboard-copy-txt">news_downloader.dataframe.shape</div>
        
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<pre>(30, 30)</pre>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">news_downloader</span><span class="o">.</span><span class="n">dataframe</span><span class="o">.</span><span class="n">columns</span>
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<div id="cell-5" class="clipboard-copy-txt">news_downloader.dataframe.columns</div>
        
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<pre>Index([&#39;description&#39;, &#39;cn:lastPubDate&#39;, &#39;dateModified&#39;, &#39;cn:dateline&#39;,
       &#39;cn:branding&#39;, &#39;section&#39;, &#39;cn:type&#39;, &#39;author&#39;, &#39;cn:source&#39;,
       &#39;cn:subtype&#39;, &#39;duration&#39;, &#39;summary&#39;, &#39;expires&#39;, &#39;cn:sectionSubType&#39;,
       &#39;cn:contentClassification&#39;, &#39;pubdateunix&#39;, &#39;_id&#39;, &#39;url&#39;, &#39;@id&#39;,
       &#39;datePublished&#39;, &#39;cn:promoImage&#39;, &#39;cn:title&#39;, &#39;cn:keyword&#39;,
       &#39;cn:liveURL&#39;, &#39;_pubDate&#39;, &#39;_type&#39;, &#39;_index&#39;, &#39;brand&#39;, &#39;hint&#39;,
       &#39;hint_detail&#39;],
      dtype=&#39;object&#39;)</pre>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">news_downloader</span><span class="o">.</span><span class="n">dataframe</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span>
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<div id="cell-6" class="clipboard-copy-txt">news_downloader.dataframe.head(2)</div>
        
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        vertical-align: middle;
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    .dataframe tbody tr th {
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</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>description</th>
      <th>cn:lastPubDate</th>
      <th>dateModified</th>
      <th>cn:dateline</th>
      <th>cn:branding</th>
      <th>section</th>
      <th>cn:type</th>
      <th>author</th>
      <th>cn:source</th>
      <th>cn:subtype</th>
      <th>...</th>
      <th>cn:promoImage</th>
      <th>cn:title</th>
      <th>cn:keyword</th>
      <th>cn:liveURL</th>
      <th>_pubDate</th>
      <th>_type</th>
      <th>_index</th>
      <th>brand</th>
      <th>hint</th>
      <th>hint_detail</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>While Leah Ellis was earning her doctorate at ...</td>
      <td>2023-06-24T10:00:01+0000</td>
      <td>2023-06-24T10:00:01+0000</td>
      <td></td>
      <td>cnbc</td>
      <td>Clean Tech</td>
      <td>cnbcnewsstory</td>
      <td>Catherine Clifford</td>
      <td>[]</td>
      <td></td>
      <td>...</td>
      <td>https://image.cnbcfm.com/api/v1/image/10726095...</td>
      <td>Meet the 33-year-old Canadian chemist and the ...</td>
      <td></td>
      <td>https://www.cnbc.com/2023/06/24/sublime-system...</td>
      <td>6/24/2023 10:00:01 PM</td>
      <td>0</td>
      <td>0</td>
      <td>cnbc</td>
      <td>NaN</td>
      <td>NaN</td>
    </tr>
    <tr>
      <th>1</th>
      <td>Amazon.com said on Friday it will take its inv...</td>
      <td>2023-06-24T04:50:41+0000</td>
      <td>2023-06-24T04:50:41+0000</td>
      <td></td>
      <td>cnbc</td>
      <td>Technology</td>
      <td>wirestory</td>
      <td></td>
      <td>[]</td>
      <td></td>
      <td>...</td>
      <td>https://image.cnbcfm.com/api/v1/image/10726178...</td>
      <td>Amazon raises investment in India to $26 billi...</td>
      <td></td>
      <td>https://www.cnbc.com/2023/06/24/amazon-commits...</td>
      <td>6/24/2023 1:49:10 PM</td>
      <td>0</td>
      <td>1</td>
      <td>cnbc</td>
      <td>NaN</td>
      <td>NaN</td>
    </tr>
  </tbody>
</table>
<p>2 rows × 30 columns</p>
</div>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">selected_columns</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;datePublished&quot;</span><span class="p">,</span> <span class="s2">&quot;cn:lastPubDate&quot;</span><span class="p">,</span> <span class="s2">&quot;dateModified&quot;</span><span class="p">,</span> <span class="s2">&quot;description&quot;</span><span class="p">,</span> <span class="s2">&quot;section&quot;</span> <span class="p">,</span><span class="s2">&quot;author&quot;</span><span class="p">,</span> <span class="s2">&quot;summary&quot;</span> <span class="p">,</span> <span class="s2">&quot;cn:title&quot;</span><span class="p">,</span> <span class="s2">&quot;cn:type&quot;</span><span class="p">]</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">dataframe</span><span class="p">[</span><span class="n">selected_columns</span><span class="p">]</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
</pre></div>
<div id="cell-7" class="clipboard-copy-txt">selected_columns = ["datePublished", "cn:lastPubDate", "dateModified", "description", "section" ,"author", "summary" , "cn:title", "cn:type"]
news_downloader.dataframe[selected_columns].head(10)</div>
        
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      <th></th>
      <th>datePublished</th>
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      <th>0</th>
      <td>2023-06-24T14:00:01+0000</td>
      <td>2023-06-24T10:00:01+0000</td>
      <td>2023-06-24T10:00:01+0000</td>
      <td>While Leah Ellis was earning her doctorate at ...</td>
      <td>Clean Tech</td>
      <td>Catherine Clifford</td>
      <td>Sublime Systems is scaling up a green cement. ...</td>
      <td>Meet the 33-year-old Canadian chemist and the ...</td>
      <td>cnbcnewsstory</td>
    </tr>
    <tr>
      <th>1</th>
      <td>2023-06-24T05:49:10+0000</td>
      <td>2023-06-24T04:50:41+0000</td>
      <td>2023-06-24T04:50:41+0000</td>
      <td>Amazon.com said on Friday it will take its inv...</td>
      <td>Technology</td>
      <td></td>
      <td>Modi and Jassy spoke about supporting Indian s...</td>
      <td>Amazon raises investment in India to $26 billi...</td>
      <td>wirestory</td>
    </tr>
    <tr>
      <th>2</th>
      <td>2023-06-23T22:12:07+0000</td>
      <td>2023-06-23T18:29:45+0000</td>
      <td>2023-06-23T18:29:45+0000</td>
      <td>As Microsoft attempts to convince regulators t...</td>
      <td>Technology</td>
      <td>Jordan Novet</td>
      <td>Microsoft has been eager to grow in mobile gam...</td>
      <td>Microsoft says it looked at acquiring Zynga bu...</td>
      <td>cnbcnewsstory</td>
    </tr>
    <tr>
      <th>3</th>
      <td>2023-06-23T21:51:15+0000</td>
      <td>2023-06-23T17:51:15+0000</td>
      <td>2023-06-23T17:51:15+0000</td>
      <td>The CEOs of Apple, Alphabet, Microsoft got a h...</td>
      <td>Technology</td>
      <td>Seema Mody</td>
      <td>Top tech execs met with Indian Prime Minister ...</td>
      <td>Apple's Tim Cook calls India 'huge opportunity...</td>
      <td>cnbcnewsstory</td>
    </tr>
    <tr>
      <th>4</th>
      <td>2023-06-23T17:32:48+0000</td>
      <td>2023-06-23T13:36:59+0000</td>
      <td>2023-06-23T13:36:59+0000</td>
      <td>Tech executives like Apple CEO Tim Cook visit ...</td>
      <td>Fast Money Halftime Report</td>
      <td>Seema Mody</td>
      <td>Tech executives like Apple CEO Tim Cook visit ...</td>
      <td>Tech CEOs meet President Biden and Indian PM M...</td>
      <td>cnbcvideo</td>
    </tr>
    <tr>
      <th>5</th>
      <td>2023-06-23T12:30:17+0000</td>
      <td>2023-06-23T13:32:42+0000</td>
      <td>2023-06-23T13:32:42+0000</td>
      <td>Anyone want to buy or sell this tech rally? To...</td>
      <td>Pro: Pro Columnists</td>
      <td>Bob Pisani</td>
      <td>Following the rebalancing of S&amp;P indexes last ...</td>
      <td>Friday could offer a once-in-a-year chance to ...</td>
      <td>cnbcnewsstory</td>
    </tr>
    <tr>
      <th>6</th>
      <td>2023-06-23T12:26:42+0000</td>
      <td>2023-06-23T11:47:06+0000</td>
      <td>2023-06-23T11:47:06+0000</td>
      <td>Here are Friday's biggest calls on Wall Street...</td>
      <td>Pro: Analyst Stock Picks</td>
      <td>Michael Bloom</td>
      <td>Here are Friday's biggest calls on Wall Street.</td>
      <td>Here are Friday's biggest analyst calls: Meta,...</td>
      <td>cnbcnewsstory</td>
    </tr>
    <tr>
      <th>7</th>
      <td>2023-06-23T06:30:01+0000</td>
      <td>2023-06-23T02:30:01+0000</td>
      <td>2023-06-23T02:30:01+0000</td>
      <td>This report is from today's CNBC Daily Open, o...</td>
      <td>Daily Open</td>
      <td>Yeo Boon Ping</td>
      <td>Investors have been lulled by a sense of secur...</td>
      <td>CNBC Daily Open: Seeking shelter in tech</td>
      <td>cnbcnewsstory</td>
    </tr>
    <tr>
      <th>8</th>
      <td>2023-06-23T05:45:33+0000</td>
      <td>2023-06-23T10:37:42+0000</td>
      <td>2023-06-23T10:37:42+0000</td>
      <td>AMSTERDAM — Artificial intelligence has a raci...</td>
      <td>Technology</td>
      <td>Ryan Browne</td>
      <td>When it comes to banking and financial service...</td>
      <td>A.I. has a discrimination problem. In banking,...</td>
      <td>cnbcnewsstory</td>
    </tr>
    <tr>
      <th>9</th>
      <td>2023-06-22T23:43:01+0000</td>
      <td>2023-06-23T01:01:10+0000</td>
      <td>2023-06-23T01:01:10+0000</td>
      <td>This report is from today's CNBC Daily Open, o...</td>
      <td>Daily Open</td>
      <td>Yeo Boon Ping</td>
      <td>Investors have been lulled by a sense of secur...</td>
      <td>CNBC Daily Open: Rate hikes and red lights</td>
      <td>cnbcnewsstory</td>
    </tr>
  </tbody>
</table>
</div>
</div>

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<h3 id="yicai">Yicai / &#31532;&#19968;&#36130;&#32463;<a class="anchor-link" href="#yicai">&#182;</a></h3>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="kn">from</span> <span class="nn">finnlp.data_sources.news.yicai_streaming</span> <span class="kn">import</span> <span class="n">Yicai_Streaming</span>
</pre></div>
<div id="cell-8" class="clipboard-copy-txt">from finnlp.data_sources.news.yicai_streaming import Yicai_Streaming</div>
        
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">news_downloader</span> <span class="o">=</span> <span class="n">Yicai_Streaming</span><span class="p">()</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">download_streaming_search</span><span class="p">(</span><span class="n">keyword</span> <span class="o">=</span> <span class="s2">&quot;茅台&quot;</span><span class="p">,</span> <span class="n">rounds</span> <span class="o">=</span> <span class="mi">3</span><span class="p">)</span>
</pre></div>
<div id="cell-9" class="clipboard-copy-txt">news_downloader = Yicai_Streaming()
news_downloader.download_streaming_search(keyword = "茅台", rounds = 3)</div>
        
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<pre>Downloading ... 0 1 2 </pre>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">news_downloader</span><span class="o">.</span><span class="n">dataframe</span><span class="o">.</span><span class="n">shape</span>
</pre></div>
<div id="cell-10" class="clipboard-copy-txt">news_downloader.dataframe.shape</div>
        
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<pre>(60, 13)</pre>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">news_downloader</span><span class="o">.</span><span class="n">dataframe</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span>
</pre></div>
<div id="cell-11" class="clipboard-copy-txt">news_downloader.dataframe.head(2)</div>
        
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  <thead>
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      <th></th>
      <th>author</th>
      <th>channelid</th>
      <th>creationDate</th>
      <th>desc</th>
      <th>id</th>
      <th>previewImage</th>
      <th>source</th>
      <th>tags</th>
      <th>title</th>
      <th>topics</th>
      <th>typeo</th>
      <th>url</th>
      <th>weight</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td></td>
      <td>100000320</td>
      <td>06-21 11:41</td>
      <td></td>
      <td>101788593</td>
      <td></td>
      <td>第一财经</td>
      <td>北斗星通;游资;龙虎;买入;通信</td>
      <td>机构抄底超讯通信  游资封板北斗星通丨龙虎榜</td>
      <td></td>
      <td>10</td>
      <td>/news/101788593.html</td>
      <td>50</td>
    </tr>
    <tr>
      <th>1</th>
      <td>[周艾琳]</td>
      <td>53</td>
      <td>06-20 21:55</td>
      <td>2003年7月，第一家QFII瑞银宣布买入宝钢股份 、上港集箱等4只蓝筹公司股票，受到了国内...</td>
      <td>101788183</td>
      <td>2023/06/e42c4bda8cc367f523764c90447ab5a3.jpg</td>
      <td>第一财经</td>
      <td>外资;A股;基金;QFII;RQFII;瑞银</td>
      <td>QFII投资A股走过20年，外资驶向何方？</td>
      <td></td>
      <td>10</td>
      <td>/news/101788183.html</td>
      <td>50</td>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">selected_columns</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;author&quot;</span><span class="p">,</span> <span class="s2">&quot;creationDate&quot;</span><span class="p">,</span> <span class="s2">&quot;desc&quot;</span> <span class="p">,</span><span class="s2">&quot;source&quot;</span><span class="p">,</span> <span class="s2">&quot;title&quot;</span><span class="p">]</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">dataframe</span><span class="p">[</span><span class="n">selected_columns</span><span class="p">]</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
</pre></div>
<div id="cell-12" class="clipboard-copy-txt">selected_columns = ["author", "creationDate", "desc" ,"source", "title"]
news_downloader.dataframe[selected_columns].head(10)</div>
        
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  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>author</th>
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    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td></td>
      <td>06-21 11:41</td>
      <td></td>
      <td>第一财经</td>
      <td>机构抄底超讯通信  游资封板北斗星通丨龙虎榜</td>
    </tr>
    <tr>
      <th>1</th>
      <td>[周艾琳]</td>
      <td>06-20 21:55</td>
      <td>2003年7月，第一家QFII瑞银宣布买入宝钢股份 、上港集箱等4只蓝筹公司股票，受到了国内...</td>
      <td>第一财经</td>
      <td>QFII投资A股走过20年，外资驶向何方？</td>
    </tr>
    <tr>
      <th>2</th>
      <td></td>
      <td>06-20 11:46</td>
      <td></td>
      <td>第一财经</td>
      <td>北向资金抄底贵州&lt;i&gt;茅台&lt;/i&gt; 游资联手封板中远海科丨龙虎榜</td>
    </tr>
    <tr>
      <th>3</th>
      <td></td>
      <td>06-20 11:45</td>
      <td></td>
      <td>第一财经</td>
      <td>22股获北向资金加仓超亿元</td>
    </tr>
    <tr>
      <th>4</th>
      <td></td>
      <td>06-20 11:36</td>
      <td></td>
      <td>第一财经</td>
      <td>北向资金抄底贵州&lt;i&gt;茅台&lt;/i&gt; 游资联手封板中远海科丨龙虎榜</td>
    </tr>
    <tr>
      <th>5</th>
      <td></td>
      <td>06-20 06:23</td>
      <td>第一财经每日早间精选热点新闻，点击「听新闻」，一键收听。</td>
      <td>第一财经</td>
      <td>布林肯结束访华，外交部美大司司长介绍情况；2023高考网上咨询周时间安排公布丨早报</td>
    </tr>
    <tr>
      <th>6</th>
      <td>[第一财经]</td>
      <td>06-19 19:06</td>
      <td></td>
      <td></td>
      <td>今日股市0619丨50大跌小票指数强势 分化局面会否延续？</td>
    </tr>
    <tr>
      <th>7</th>
      <td></td>
      <td>06-19 19:05</td>
      <td></td>
      <td>第一财经</td>
      <td>今日股市0619丨50大跌小票指数强势 分化局面会否延续？</td>
    </tr>
    <tr>
      <th>8</th>
      <td>[一财资讯]</td>
      <td>06-19 17:46</td>
      <td>净买入额居前三的是贵州&lt;i&gt;茅台&lt;/i&gt;、药明康德、新易盛，分别获净买入3.48亿元、3.3...</td>
      <td>第一财经</td>
      <td>北向资金净卖出14.47亿元，贵州&lt;i&gt;茅台&lt;/i&gt;、药明康德等获加仓</td>
    </tr>
    <tr>
      <th>9</th>
      <td></td>
      <td>06-19 15:39</td>
      <td></td>
      <td>第一财经</td>
      <td>三大指数小幅收跌 TMT赛道持续大涨｜尾市盘点</td>
    </tr>
  </tbody>
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<h3 id="investor-place">Investor Place<a class="anchor-link" href="#investor-place">&#182;</a></h3>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="kn">from</span> <span class="nn">finnlp.data_sources.news.investorplace_streaming</span> <span class="kn">import</span> <span class="n">InvestorPlace_Streaming</span>
</pre></div>
<div id="cell-13" class="clipboard-copy-txt">from finnlp.data_sources.news.investorplace_streaming import InvestorPlace_Streaming</div>
        
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">news_downloader</span> <span class="o">=</span> <span class="n">InvestorPlace_Streaming</span><span class="p">()</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">download_streaming_search</span><span class="p">(</span><span class="n">keyword</span> <span class="o">=</span> <span class="s2">&quot;apple&quot;</span><span class="p">,</span> <span class="n">rounds</span> <span class="o">=</span> <span class="mi">3</span><span class="p">)</span>
</pre></div>
<div id="cell-14" class="clipboard-copy-txt">news_downloader = InvestorPlace_Streaming()
news_downloader.download_streaming_search(keyword = "apple", rounds = 3)</div>
        
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<pre>Downloading ... 0 1 2 </pre>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">selected_columns</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;title&quot;</span><span class="p">,</span> <span class="s2">&quot;time&quot;</span> <span class="p">,</span><span class="s2">&quot;author&quot;</span><span class="p">,</span> <span class="s2">&quot;summary&quot;</span><span class="p">]</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">dataframe</span><span class="p">[</span><span class="n">selected_columns</span><span class="p">]</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
</pre></div>
<div id="cell-15" class="clipboard-copy-txt">selected_columns = ["title", "time" ,"author", "summary"]
news_downloader.dataframe[selected_columns].head(10)</div>
        
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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>title</th>
      <th>time</th>
      <th>author</th>
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    <tr>
      <th>0</th>
      <td>[Trillion-Dollar Tech: 3 Stocks Poised for Unp...</td>
      <td>Jun 19, 2023</td>
      <td>Faisal Humayun, InvestorPlace Contributor</td>
      <td>These are the tech stocks to buy for multibagg...</td>
    </tr>
    <tr>
      <th>1</th>
      <td>[Trillion-Dollar Tech: 3 Stocks Poised for Unp...</td>
      <td>Jun 22, 2023</td>
      <td>Chris MacDonald, InvestorPlace Contributor</td>
      <td>Warren Buffett is undoubtedly one of the great...</td>
    </tr>
    <tr>
      <th>2</th>
      <td>[Invest Like a Billionaire: 3 Long-Term Stocks...</td>
      <td>Jun 18, 2023</td>
      <td>Joel Baglole, InvestorPlace Contributor</td>
      <td>With markets now recovering from the downturn ...</td>
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    <tr>
      <th>3</th>
      <td>[Invest Like a Billionaire: 3 Long-Term Stocks...</td>
      <td>Jun 16, 2023</td>
      <td>Louis Navellier and the InvestorPlace Research...</td>
      <td>The best tech stocks to watch are involved in ...</td>
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      <th>4</th>
      <td>[3 Tech Titans Leading the Charge Toward $10 T...</td>
      <td>Jun 19, 2023</td>
      <td>Will Ashworth, InvestorPlace Contributor</td>
      <td>Avoiding bad stocks requires investors to get ...</td>
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      <th>5</th>
      <td>[3 Tech Titans Leading the Charge Toward $10 T...</td>
      <td>Jun 19, 2023</td>
      <td>Tyrik Torres, InvestorPlace Contributor</td>
      <td>While AI software companies tend to get more b...</td>
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      <th>6</th>
      <td>[7 Tech Stocks to Watch Out For in 2023 … and ...</td>
      <td>Jun 16, 2023</td>
      <td>Chris MacDonald, InvestorPlace Contributor</td>
      <td>Many long-term conservative investors pay atte...</td>
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      <th>7</th>
      <td>[7 Tech Stocks to Watch Out For in 2023 … and ...</td>
      <td>Jun 16, 2023</td>
      <td>Louis Navellier and the InvestorPlace Research...</td>
      <td>Every stock has its ups and downs, but reliabl...</td>
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      <th>8</th>
      <td>[3 Smart Takes on 3 Dumb Stocks]</td>
      <td>Jun 23, 2023</td>
      <td>Samuel O'Brient, InvestorPlace Financial News ...</td>
      <td>Even as tech stocks rally, short sellers are s...</td>
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      <th>9</th>
      <td>[3 Smart Takes on 3 Dumb Stocks]</td>
      <td>Jun 18, 2023</td>
      <td>Chris Markoch, InvestorPlace Contributor</td>
      <td>Here are seven high cash flow stocks that prov...</td>
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<h3 id="guru-focus">Guru Focus<a class="anchor-link" href="#guru-focus">&#182;</a></h3>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="kn">from</span> <span class="nn">finnlp.data_sources.news.gurufocus_streaming</span> <span class="kn">import</span> <span class="n">GuruFocus_Streaming</span>
</pre></div>
<div id="cell-16" class="clipboard-copy-txt">from finnlp.data_sources.news.gurufocus_streaming import GuruFocus_Streaming</div>
        
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">news_downloader</span> <span class="o">=</span> <span class="n">GuruFocus_Streaming</span><span class="p">()</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">download_streaming_search</span><span class="p">(</span><span class="n">keyword</span> <span class="o">=</span> <span class="s2">&quot;AAPL&quot;</span><span class="p">,</span> <span class="n">rounds</span> <span class="o">=</span> <span class="mi">3</span><span class="p">)</span>
</pre></div>
<div id="cell-17" class="clipboard-copy-txt">news_downloader = GuruFocus_Streaming()
news_downloader.download_streaming_search(keyword = "AAPL", rounds = 3)</div>
        
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<pre>Only support first page now!
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">selected_columns</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;title&quot;</span><span class="p">,</span> <span class="s2">&quot;view&quot;</span> <span class="p">,</span><span class="s2">&quot;source&quot;</span><span class="p">,</span> <span class="s2">&quot;datetime&quot;</span><span class="p">]</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">dataframe</span><span class="p">[</span><span class="n">selected_columns</span><span class="p">]</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
</pre></div>
<div id="cell-18" class="clipboard-copy-txt">selected_columns = ["title", "view" ,"source", "datetime"]
news_downloader.dataframe[selected_columns].head(10)</div>
        
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      <th>0</th>
      <td>3 Magic Formula Stocks Popular With Gurus</td>
      <td>0 Views</td>
      <td>Margaret Moran</td>
      <td>2023-06-23 17:38</td>
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      <th>1</th>
      <td>Jeremy Grantham: The Super Bubble Is About to Pop</td>
      <td>60 Views</td>
      <td>Ben Alaimo</td>
      <td>2023-06-23 09:21</td>
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      <th>2</th>
      <td>5 High GF Score Stocks That Outperformed the M...</td>
      <td>106 Views</td>
      <td>James Li</td>
      <td>2023-06-21 19:36</td>
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      <th>3</th>
      <td>New Feature: DuPont Analysis Chart for Enhance...</td>
      <td>259 Views</td>
      <td>Vera Yuan</td>
      <td>2023-06-21 16:55</td>
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      <td>The Most-Sold Guru Stocks of the 1st Quarter</td>
      <td>261 Views</td>
      <td>Margaret Moran</td>
      <td>2023-06-16 17:32</td>
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      <th>5</th>
      <td>AI Revolution and Debt Ceiling Resolution</td>
      <td>198 Views</td>
      <td>Wade W. Slome, CFA, CFP</td>
      <td>2023-06-05 21:03</td>
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      <th>6</th>
      <td>Nvidia vs. ARK Invest: Which Is the Better Gro...</td>
      <td>332 Views</td>
      <td>Joey Frenette</td>
      <td>2023-05-27 02:05</td>
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    <tr>
      <th>7</th>
      <td>Top 5 1st Quarter Trades of CYPRESS ASSET MANA...</td>
      <td>0 Views</td>
      <td>GuruFocus Editor</td>
      <td>2023-05-26 14:08</td>
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    <tr>
      <th>8</th>
      <td>Mill Creek Capital Advisors, LLC Buys 2, Sells...</td>
      <td>0 Views</td>
      <td>GuruFocus Editor</td>
      <td>2023-05-25 18:10</td>
    </tr>
    <tr>
      <th>9</th>
      <td>Jim Simons' Renaissance Technologies Chops Pos...</td>
      <td>380 Views</td>
      <td>James Li</td>
      <td>2023-05-24 18:43</td>
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<h3 id="alliance-news">Alliance News<a class="anchor-link" href="#alliance-news">&#182;</a></h3>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="kn">from</span> <span class="nn">finnlp.data_sources.news.alliancenews_streaming</span> <span class="kn">import</span> <span class="n">AllianceNews_Streaming</span>
</pre></div>
<div id="cell-19" class="clipboard-copy-txt">from finnlp.data_sources.news.alliancenews_streaming import AllianceNews_Streaming</div>
        
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">news_downloader</span> <span class="o">=</span> <span class="n">AllianceNews_Streaming</span><span class="p">()</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">download_streaming_search</span><span class="p">(</span><span class="n">rounds</span> <span class="o">=</span> <span class="mi">3</span><span class="p">)</span>
</pre></div>
<div id="cell-20" class="clipboard-copy-txt">news_downloader = AllianceNews_Streaming()
news_downloader.download_streaming_search(rounds = 3)</div>
        
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">news_downloader</span><span class="o">.</span><span class="n">dataframe</span><span class="o">.</span><span class="n">shape</span>
</pre></div>
<div id="cell-21" class="clipboard-copy-txt">news_downloader.dataframe.shape</div>
        
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">news_downloader</span><span class="o">.</span><span class="n">dataframe</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
</pre></div>
<div id="cell-22" class="clipboard-copy-txt">news_downloader.dataframe.head(1)</div>
        
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<table border="1" class="dataframe">
  <thead>
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      <th></th>
      <th>urlId</th>
      <th>title</th>
      <th>summary</th>
      <th>created</th>
      <th>updated</th>
      <th>thumbnailUrl</th>
      <th>source</th>
      <th>taxonomies</th>
      <th>type</th>
      <th>author</th>
      <th>meta</th>
      <th>sponsor</th>
      <th>parent</th>
      <th>contentId</th>
      <th>displayTaxonomies</th>
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      <th>0</th>
      <td>/news/new-york-market-close-stocks-down-dollar...</td>
      <td>NEW YORK MARKET CLOSE: Stocks down, dollar up ...</td>
      <td>None</td>
      <td>2023-06-23T21:18:34</td>
      <td>2023-06-23T21:18:34</td>
      <td>None</td>
      <td>{'code': 'ALLIANCE', 'title': 'Alliance News',...</td>
      <td>[{'termId': 'CTMRR', 'parentTermId': None, 'ti...</td>
      <td>news</td>
      <td>None</td>
      <td>{'title': 'NEW YORK MARKET CLOSE: Stocks down,...</td>
      <td>None</td>
      <td>None</td>
      <td>al1687551514259519100</td>
      <td>[{'termId': 'TPCOM', 'parentTermId': 'PTMKT', ...</td>
      <td>None</td>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">selected_columns</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;created&quot;</span><span class="p">,</span> <span class="s2">&quot;updated&quot;</span><span class="p">,</span> <span class="s2">&quot;title&quot;</span><span class="p">,</span> <span class="s2">&quot;summary&quot;</span><span class="p">,</span> <span class="s2">&quot;meta&quot;</span><span class="p">]</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">dataframe</span><span class="p">[</span><span class="n">selected_columns</span><span class="p">]</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
</pre></div>
<div id="cell-23" class="clipboard-copy-txt">selected_columns = ["created", "updated", "title", "summary", "meta"]
news_downloader.dataframe[selected_columns].head(10)</div>
        
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      <th>0</th>
      <td>2023-06-23T21:18:34</td>
      <td>2023-06-23T21:18:34</td>
      <td>NEW YORK MARKET CLOSE: Stocks down, dollar up ...</td>
      <td>None</td>
      <td>{'title': 'NEW YORK MARKET CLOSE: Stocks down,...</td>
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      <th>1</th>
      <td>2023-06-23T19:34:05</td>
      <td>2023-06-23T19:34:05</td>
      <td>IN BRIEF: Blackstone Loan Financing proposes w...</td>
      <td>None</td>
      <td>{'title': 'IN BRIEF: Blackstone Loan Financing...</td>
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    <tr>
      <th>2</th>
      <td>2023-06-23T18:34:41</td>
      <td>2023-06-23T18:34:41</td>
      <td>IN BRIEF: Bonhill expects to complete sale of ...</td>
      <td>None</td>
      <td>{'title': 'IN BRIEF: Bonhill expects to comple...</td>
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      <th>3</th>
      <td>2023-06-23T18:01:27</td>
      <td>2023-06-23T18:01:27</td>
      <td>UPDATE: SRT Marine Systems raises GBP4.6 milli...</td>
      <td>None</td>
      <td>{'title': 'UPDATE: SRT Marine Systems raises G...</td>
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    <tr>
      <th>4</th>
      <td>2023-06-23T18:00:27</td>
      <td>2023-06-23T18:00:27</td>
      <td>IN BRIEF: New Energy One Acquisition confirms ...</td>
      <td>None</td>
      <td>{'title': 'IN BRIEF: New Energy One Acquisitio...</td>
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      <th>5</th>
      <td>2023-06-23T17:41:15</td>
      <td>2023-06-23T17:41:15</td>
      <td>IN BRIEF: Kropz makes draw down request on bri...</td>
      <td>None</td>
      <td>{'title': 'IN BRIEF: Kropz makes draw down req...</td>
    </tr>
    <tr>
      <th>6</th>
      <td>2023-06-23T17:31:17</td>
      <td>2023-06-23T17:31:17</td>
      <td>IN BRIEF: XPS Pensions discusses National Pens...</td>
      <td>None</td>
      <td>{'title': 'IN BRIEF: XPS Pensions discusses Na...</td>
    </tr>
    <tr>
      <th>7</th>
      <td>2023-06-23T17:25:54</td>
      <td>2023-06-23T17:25:54</td>
      <td>DIRECTOR DEALINGS: GSK CFO buys shares worth G...</td>
      <td>None</td>
      <td>{'title': 'DIRECTOR DEALINGS: GSK CFO buys sha...</td>
    </tr>
    <tr>
      <th>8</th>
      <td>2023-06-23T17:21:29</td>
      <td>2023-06-23T17:21:29</td>
      <td>IN BRIEF: Gilead Sciences says test results sh...</td>
      <td>None</td>
      <td>{'title': 'IN BRIEF: Gilead Sciences says test...</td>
    </tr>
    <tr>
      <th>9</th>
      <td>2023-06-23T17:07:24</td>
      <td>2023-06-23T17:07:24</td>
      <td>IN THE KNOW: AB Foods "fundamentally strong" w...</td>
      <td>None</td>
      <td>{'title': 'IN THE KNOW: AB Foods "fundamentall...</td>
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<h3 id="talk-market">Talk Market<a class="anchor-link" href="#talk-market">&#182;</a></h3>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="kn">from</span> <span class="nn">finnlp.data_sources.news.talkmarkets_streaming</span> <span class="kn">import</span> <span class="n">TalkMarkets_Streaming</span>
</pre></div>
<div id="cell-24" class="clipboard-copy-txt">from finnlp.data_sources.news.talkmarkets_streaming import TalkMarkets_Streaming</div>
        
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">news_downloader</span> <span class="o">=</span> <span class="n">TalkMarkets_Streaming</span><span class="p">()</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">download_streaming_search</span><span class="p">(</span><span class="n">keyword</span> <span class="o">=</span> <span class="s2">&quot;apple&quot;</span><span class="p">,</span> <span class="n">rounds</span> <span class="o">=</span> <span class="mi">3</span><span class="p">)</span>
</pre></div>
<div id="cell-25" class="clipboard-copy-txt">news_downloader = TalkMarkets_Streaming()
news_downloader.download_streaming_search(keyword = "apple", rounds = 3)</div>
        
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<pre>Downloading... 0 1 2 </pre>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">news_downloader</span><span class="o">.</span><span class="n">dataframe</span><span class="o">.</span><span class="n">shape</span>
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<div id="cell-26" class="clipboard-copy-txt">news_downloader.dataframe.shape</div>
        
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<pre>(60, 12)</pre>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">news_downloader</span><span class="o">.</span><span class="n">dataframe</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
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<div id="cell-27" class="clipboard-copy-txt">news_downloader.dataframe.head(1)</div>
        
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      <td>http://www.google.com/search?q=cache:PUjyIRJA8...</td>
      <td>https://www.google.com/url?client=internal-ele...</td>
      <td>23 hours ago &lt;b&gt;...&lt;/b&gt; &lt;b&gt;Apple&lt;/b&gt;, 187, 3.0...</td>
      <td>23 hours ago ... Apple, 187, 3.04, 1.65%, 187....</td>
      <td>Equitymaster India | Sensex Today Trades Lower...</td>
      <td>Equitymaster India | Sensex Today Trades Lower...</td>
      <td>https://talkmarkets.com/.../sensex-today-trade...</td>
      <td>https://talkmarkets.com/content/global-markets...</td>
      <td>https://talkmarkets.com/content/global-markets...</td>
      <td>talkmarkets.com</td>
      <td>{'cseImage': {'src': 'https://www.eqimg.com/im...</td>
      <td>{'host': 'talkmarkets.com', 'crumbs': ['sensex...</td>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">selected_columns</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;content&quot;</span><span class="p">,</span> <span class="s2">&quot;url&quot;</span><span class="p">,</span> <span class="s2">&quot;clicktrackUrl&quot;</span><span class="p">]</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">dataframe</span><span class="p">[</span><span class="n">selected_columns</span><span class="p">]</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
</pre></div>
<div id="cell-28" class="clipboard-copy-txt">selected_columns = ["content", "url", "clicktrackUrl"]
news_downloader.dataframe[selected_columns].head(10)</div>
        
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      <th>0</th>
      <td>23 hours ago &lt;b&gt;...&lt;/b&gt; &lt;b&gt;Apple&lt;/b&gt;, 187, 3.0...</td>
      <td>https://talkmarkets.com/content/global-markets...</td>
      <td>https://www.google.com/url?client=internal-ele...</td>
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    <tr>
      <th>1</th>
      <td>1 day ago &lt;b&gt;...&lt;/b&gt; Get Adobe Inc. (ADBE:NASD...</td>
      <td>https://talkmarkets.com/symbol/adbe/portal-wid...</td>
      <td>https://www.google.com/url?client=internal-ele...</td>
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      <th>2</th>
      <td>1 day ago &lt;b&gt;...&lt;/b&gt; Get Starbucks Corp (SBUX:...</td>
      <td>https://talkmarkets.com/symbol/sbux/portal-wid...</td>
      <td>https://www.google.com/url?client=internal-ele...</td>
    </tr>
    <tr>
      <th>3</th>
      <td>10 hours ago &lt;b&gt;...&lt;/b&gt; Wednesday&amp;#39;s top an...</td>
      <td>https://talkmarkets.com/symbol/pypl/portal-wid...</td>
      <td>https://www.google.com/url?client=internal-ele...</td>
    </tr>
    <tr>
      <th>4</th>
      <td>20 hours ago &lt;b&gt;...&lt;/b&gt; &lt;b&gt;Apple&lt;/b&gt; (AAPL). &lt;...</td>
      <td>https://talkmarkets.com/content/stocks--equiti...</td>
      <td>https://www.google.com/url?client=internal-ele...</td>
    </tr>
    <tr>
      <th>5</th>
      <td>2 days ago &lt;b&gt;...&lt;/b&gt; Friday&amp;#39;s top analyst...</td>
      <td>https://talkmarkets.com/symbol/sofi/portal-wid...</td>
      <td>https://www.google.com/url?client=internal-ele...</td>
    </tr>
    <tr>
      <th>6</th>
      <td>2 days ago &lt;b&gt;...&lt;/b&gt; Get Enphase Energy Inc (...</td>
      <td>https://talkmarkets.com/symbol/enph/portal-wid...</td>
      <td>https://www.google.com/url?client=internal-ele...</td>
    </tr>
    <tr>
      <th>7</th>
      <td>3 days ago &lt;b&gt;...&lt;/b&gt; &lt;b&gt;Apple&lt;/b&gt; Inc. design...</td>
      <td>https://talkmarkets.com/contributor/jimvanmeer...</td>
      <td>https://www.google.com/url?client=internal-ele...</td>
    </tr>
    <tr>
      <th>8</th>
      <td>3 days ago &lt;b&gt;...&lt;/b&gt; &lt;b&gt;Apple&lt;/b&gt; Inc. design...</td>
      <td>https://talkmarkets.com/content/stocks--equiti...</td>
      <td>https://www.google.com/url?client=internal-ele...</td>
    </tr>
    <tr>
      <th>9</th>
      <td>5 Jan 2023 &lt;b&gt;...&lt;/b&gt; Get Amazon.com Inc (AMZN...</td>
      <td>https://talkmarkets.com/symbol/amzn/portal-wid...</td>
      <td>https://www.google.com/url?client=internal-ele...</td>
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<h3 id="the-fly">The Fly<a class="anchor-link" href="#the-fly">&#182;</a></h3>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="kn">from</span> <span class="nn">finnlp.data_sources.news.thefly_streaming</span> <span class="kn">import</span> <span class="n">TheFly_Streaming</span>
</pre></div>
<div id="cell-29" class="clipboard-copy-txt">from finnlp.data_sources.news.thefly_streaming import TheFly_Streaming</div>
        
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">news_downloader</span> <span class="o">=</span> <span class="n">TheFly_Streaming</span><span class="p">()</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">download_streaming_search</span><span class="p">(</span><span class="n">keyword</span> <span class="o">=</span> <span class="s2">&quot;AAPL&quot;</span><span class="p">,</span> <span class="n">rounds</span> <span class="o">=</span> <span class="mi">3</span><span class="p">)</span>
</pre></div>
<div id="cell-30" class="clipboard-copy-txt">news_downloader = TheFly_Streaming()
news_downloader.download_streaming_search(keyword = "AAPL", rounds = 3)</div>
        
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<pre>c:\ProgramData\Anaconda3\lib\site-packages\urllib3\connectionpool.py:1045: InsecureRequestWarning: Unverified HTTPS request is being made to host &#39;thefly.com&#39;. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/1.26.x/advanced-usage.html#ssl-warnings
  warnings.warn(
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<pre>Only support the first page now!
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">selected_columns</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;title&quot;</span><span class="p">,</span> <span class="s2">&quot;stock&quot;</span><span class="p">,</span> <span class="s2">&quot;abstract&quot;</span><span class="p">,</span> <span class="s2">&quot;date&quot;</span><span class="p">,</span> <span class="s2">&quot;time&quot;</span><span class="p">]</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">dataframe</span><span class="p">[</span><span class="n">selected_columns</span><span class="p">]</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
</pre></div>
<div id="cell-31" class="clipboard-copy-txt">selected_columns = ["title", "stock", "abstract", "date", "time"]
news_downloader.dataframe[selected_columns].head(10)</div>
        
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        vertical-align: middle;
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        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>title</th>
      <th>stock</th>
      <th>abstract</th>
      <th>date</th>
      <th>time</th>
    </tr>
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      <th>0</th>
      <td>Apple in talks to launch Apple Card in India, ...</td>
      <td>AAPL</td>
      <td>Apple is in talks to…</td>
      <td>06/23/23</td>
      <td>05:37</td>
    </tr>
    <tr>
      <th>1</th>
      <td>Apple says visionOS software development kit n...</td>
      <td>AAPL</td>
      <td>Apple announced the…</td>
      <td>06/21/23</td>
      <td>16:03</td>
    </tr>
    <tr>
      <th>2</th>
      <td>Apple to create spatial experiences for Apple ...</td>
      <td>AAPL</td>
      <td>Apple "announced the…</td>
      <td>06/21/23</td>
      <td>16:00</td>
    </tr>
    <tr>
      <th>3</th>
      <td>Notable open interest changes for June 21st</td>
      <td>TSLA NVDA AAPL AMZN</td>
      <td>Tuesday's total…</td>
      <td>06/21/23</td>
      <td>08:55</td>
    </tr>
    <tr>
      <th>4</th>
      <td>What You Missed This Week in Video Games</td>
      <td>TCEHY TTWO EA CCOEY UBSFY CMCSK CMCSA RBLX AAP...</td>
      <td>"Game On" is The Fly's…</td>
      <td>06/20/23</td>
      <td>12:11</td>
    </tr>
    <tr>
      <th>5</th>
      <td>Notable open interest changes for June 20th</td>
      <td>TSLA AMC AAPL NVDA</td>
      <td>Friday's total…</td>
      <td>06/20/23</td>
      <td>08:55</td>
    </tr>
    <tr>
      <th>6</th>
      <td>Apple call buyer realizes 20% same-day gains</td>
      <td>AAPL</td>
      <td>Notable profits for the…</td>
      <td>06/16/23</td>
      <td>08:00</td>
    </tr>
    <tr>
      <th>7</th>
      <td>Notable open interest changes for June 15th</td>
      <td>TSLA NVDA SOFI AAPL</td>
      <td>Wednesday's total…</td>
      <td>06/15/23</td>
      <td>08:55</td>
    </tr>
    <tr>
      <th>8</th>
      <td>US senators propose bill to eliminate Section ...</td>
      <td>GOOG MSFT AMZN AAPL NVDA IBM META INTC</td>
      <td>"U.S. Senators Josh…</td>
      <td>06/14/23</td>
      <td>17:54</td>
    </tr>
    <tr>
      <th>9</th>
      <td>#SocialStocks: Twitter skips out on rent and G...</td>
      <td>TWTR AAPL META GOOGL GOOG ZM RBLX PINS</td>
      <td>Welcome to…</td>
      <td>06/14/23</td>
      <td>15:57</td>
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<h3 id="tip-rank">Tip Rank<a class="anchor-link" href="#tip-rank">&#182;</a></h3>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="kn">from</span> <span class="nn">finnlp.data_sources.news.tipranks_streaming</span> <span class="kn">import</span> <span class="n">TipRanks_Streaming</span>
</pre></div>
<div id="cell-32" class="clipboard-copy-txt">from finnlp.data_sources.news.tipranks_streaming import TipRanks_Streaming</div>
        
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">news_downloader</span> <span class="o">=</span> <span class="n">TipRanks_Streaming</span><span class="p">()</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">download_streaming_search</span><span class="p">(</span><span class="n">keyword</span> <span class="o">=</span> <span class="s2">&quot;apple&quot;</span><span class="p">,</span> <span class="n">rounds</span> <span class="o">=</span> <span class="mi">3</span><span class="p">)</span>
</pre></div>
<div id="cell-33" class="clipboard-copy-txt">news_downloader = TipRanks_Streaming()
news_downloader.download_streaming_search(keyword = "apple", rounds = 3)</div>
        
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<pre>Downloading: 0 1 2 </pre>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">news_downloader</span><span class="o">.</span><span class="n">dataframe</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span>
</pre></div>
<div id="cell-34" class="clipboard-copy-txt">news_downloader.dataframe.head(2)</div>
        
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    .dataframe tbody tr th {
        vertical-align: top;
    }

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        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>stocks</th>
      <th>_id</th>
      <th>author</th>
      <th>category</th>
      <th>date</th>
      <th>description</th>
      <th>image</th>
      <th>isLocked</th>
      <th>link</th>
      <th>lockType</th>
      <th>slug</th>
      <th>sticky</th>
      <th>thumbnail</th>
      <th>title</th>
      <th>topics</th>
      <th>timeAgo</th>
      <th>badge</th>
      <th>id</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>[{'ticker': 'AAPL', 'market': None}]</td>
      <td>582530</td>
      <td>{'slug': 'steveanderson'}</td>
      <td>{'slug': 'news', 'title': 'Market News'}</td>
      <td>2023-06-22T19:52:41.000Z</td>
      <td>&lt;p&gt;Those who regularly follow Apple stock (NAS...</td>
      <td>{'src': 'https://blog.tipranks.com/wp-content/...</td>
      <td>True</td>
      <td>https://www.tipranks.com/news/aapl-notches-up-...</td>
      <td>GraceCount</td>
      <td>aapl-notches-up-following-barclays-comments</td>
      <td>False</td>
      <td>{'src': 'https://blog.tipranks.com/wp-content/...</td>
      <td>AAPL Notches Up Following Barclays Comments</td>
      <td>[{'id': 0, 'type': 'stock', 'title': 'AAPL', '...</td>
      <td>13h</td>
      <td>None</td>
      <td>582530</td>
    </tr>
    <tr>
      <th>1</th>
      <td>[{'ticker': 'AAPL', 'market': None}, {'ticker'...</td>
      <td>579043</td>
      <td>{'slug': 'amit-singh'}</td>
      <td>{'slug': 'article', 'title': 'Stock Analysis &amp;...</td>
      <td>2023-06-19T15:30:38.000Z</td>
      <td>&lt;p&gt;Affirm Holdings (NASDAQ:AFRM) stock recover...</td>
      <td>{'src': 'https://blog.tipranks.com/wp-content/...</td>
      <td>True</td>
      <td>https://www.tipranks.com/news/article/affirm-s...</td>
      <td>GraceCount</td>
      <td>affirm-stock-has-risen-swiftly-will-it-beat-ap...</td>
      <td>False</td>
      <td>{'src': 'https://blog.tipranks.com/wp-content/...</td>
      <td>Affirm Stock Has Risen Swiftly. Will It Beat A...</td>
      <td>[{'id': 0, 'type': 'stock', 'title': 'AAPL', '...</td>
      <td>4d</td>
      <td>None</td>
      <td>579043</td>
    </tr>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">selected_columns</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;stocks&quot;</span><span class="p">,</span> <span class="s2">&quot;date&quot;</span><span class="p">,</span> <span class="s2">&quot;author&quot;</span><span class="p">,</span> <span class="s2">&quot;title&quot;</span><span class="p">,</span> <span class="s2">&quot;description&quot;</span><span class="p">]</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">dataframe</span><span class="p">[</span><span class="n">selected_columns</span><span class="p">]</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
</pre></div>
<div id="cell-35" class="clipboard-copy-txt">selected_columns = ["stocks", "date", "author", "title", "description"]
news_downloader.dataframe[selected_columns].head(10)</div>
        
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        text-align: right;
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</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>stocks</th>
      <th>date</th>
      <th>author</th>
      <th>title</th>
      <th>description</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>[{'ticker': 'AAPL', 'market': None}]</td>
      <td>2023-06-22T19:52:41.000Z</td>
      <td>{'slug': 'steveanderson'}</td>
      <td>AAPL Notches Up Following Barclays Comments</td>
      <td>&lt;p&gt;Those who regularly follow Apple stock (NAS...</td>
    </tr>
    <tr>
      <th>1</th>
      <td>[{'ticker': 'AAPL', 'market': None}, {'ticker'...</td>
      <td>2023-06-19T15:30:38.000Z</td>
      <td>{'slug': 'amit-singh'}</td>
      <td>Affirm Stock Has Risen Swiftly. Will It Beat A...</td>
      <td>&lt;p&gt;Affirm Holdings (NASDAQ:AFRM) stock recover...</td>
    </tr>
    <tr>
      <th>2</th>
      <td>[{'ticker': 'AAPL', 'market': None}, {'ticker'...</td>
      <td>2023-06-16T20:51:11.000Z</td>
      <td>{'slug': 'joey-frenette'}</td>
      <td>Apple Stock (NASDAQ:AAPL): Expectations Too Mo...</td>
      <td>&lt;p&gt;Apple (NASDAQ:AAPL) stock recently hit a ne...</td>
    </tr>
    <tr>
      <th>3</th>
      <td>[{'ticker': 'AAPL', 'market': None}, {'ticker'...</td>
      <td>2023-06-16T08:32:40.000Z</td>
      <td>{'slug': 'sheryl-sheth'}</td>
      <td>Lost the Nvidia and Apple Boom? Microsoft (NAS...</td>
      <td>&lt;p&gt;Think you lost the chance to become wealthy...</td>
    </tr>
    <tr>
      <th>4</th>
      <td>[{'ticker': 'AAPL', 'market': None}, {'ticker'...</td>
      <td>2023-06-15T19:20:48.000Z</td>
      <td>{'slug': 'joey-frenette'}</td>
      <td>Unity Software (NASDAQ:U): Apple Vision Pro Pa...</td>
      <td>&lt;p&gt;Unity Software (NASDAQ:U) rallied 17% when ...</td>
    </tr>
    <tr>
      <th>5</th>
      <td>[{'ticker': 'AAPL', 'market': None}, {'ticker'...</td>
      <td>2023-06-15T00:53:16.000Z</td>
      <td>{'slug': 'joey-frenette'}</td>
      <td>Investing in Apple’s (NASDAQ:AAPL) Ecosystem: ...</td>
      <td>&lt;p&gt;Apple (NASDAQ:AAPL) has been on an unbeliev...</td>
    </tr>
    <tr>
      <th>6</th>
      <td>[{'ticker': 'AAPL', 'market': None}]</td>
      <td>2023-06-13T15:13:40.000Z</td>
      <td>{'slug': 'vince-condarcuri'}</td>
      <td>AAPL Stock Slips after Analyst Downgrade</td>
      <td>&lt;p&gt;Despite outperforming the S&amp;amp;P 500 with ...</td>
    </tr>
    <tr>
      <th>7</th>
      <td>[{'ticker': 'AAPL', 'market': None}]</td>
      <td>2023-06-10T15:09:23.000Z</td>
      <td>{'slug': 'martyshtrubel'}</td>
      <td>Apple Stock Gets a New Street-High Price Target</td>
      <td>&lt;p&gt;Apple’s (NASDAQ:AAPL) virtual reality and a...</td>
    </tr>
    <tr>
      <th>8</th>
      <td>[{'ticker': 'AAPL', 'market': None}, {'ticker'...</td>
      <td>2023-06-09T09:46:28.000Z</td>
      <td>{'slug': 'amit-singh'}</td>
      <td>NVDA to META: Insiders Capitalise on Tech Stoc...</td>
      <td>&lt;p&gt;Technology stocks rebounded strongly in 202...</td>
    </tr>
    <tr>
      <th>9</th>
      <td>[{'ticker': 'AAPL', 'market': None}, {'ticker'...</td>
      <td>2023-06-08T18:20:20.000Z</td>
      <td>{'slug': 'michaelbyrne'}</td>
      <td>Apple Stock is on Fire. Invest in it with Thes...</td>
      <td>&lt;p&gt;Apple (NASDAQ:AAPL) stock is off to a gain ...</td>
    </tr>
  </tbody>
</table>
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<h3 id="market-watch-date-range">Market Watch (Date Range)<a class="anchor-link" href="#market-watch-date-range">&#182;</a></h3>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="kn">from</span> <span class="nn">finnlp.data_sources.news.marketwatch_date_range</span> <span class="kn">import</span> <span class="n">MarketWatch_Date_Range</span>
</pre></div>
<div id="cell-36" class="clipboard-copy-txt">from finnlp.data_sources.news.marketwatch_date_range import MarketWatch_Date_Range</div>
        
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">start_date</span> <span class="o">=</span> <span class="s2">&quot;2022-06-01&quot;</span>
<span class="n">end_date</span> <span class="o">=</span> <span class="s2">&quot;2022-06-30&quot;</span>
<span class="n">keyword</span> <span class="o">=</span> <span class="s2">&quot;apple&quot;</span>
</pre></div>
<div id="cell-37" class="clipboard-copy-txt">start_date = "2022-06-01"
end_date = "2022-06-30"
keyword = "apple"</div>
        
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">news_downloader</span> <span class="o">=</span> <span class="n">MarketWatch_Date_Range</span><span class="p">()</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">download_date_range_search</span><span class="p">(</span><span class="n">keyword</span> <span class="o">=</span> <span class="s2">&quot;apple&quot;</span><span class="p">,</span> <span class="n">start_date</span> <span class="o">=</span> <span class="n">start_date</span><span class="p">,</span> <span class="n">end_date</span> <span class="o">=</span> <span class="n">end_date</span><span class="p">)</span>
</pre></div>
<div id="cell-38" class="clipboard-copy-txt">news_downloader = MarketWatch_Date_Range()
news_downloader.download_date_range_search(keyword = "apple", start_date = start_date, end_date = end_date)</div>
        
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<pre>Only support the first page now!
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">selected_columns</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;title&quot;</span><span class="p">,</span> <span class="s2">&quot;time&quot;</span><span class="p">,</span> <span class="s2">&quot;author&quot;</span><span class="p">]</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">dataframe</span><span class="p">[</span><span class="n">selected_columns</span><span class="p">]</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
</pre></div>
<div id="cell-39" class="clipboard-copy-txt">selected_columns = ["title", "time", "author"]
news_downloader.dataframe[selected_columns].head(10)</div>
        
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      <th>0</th>
      <td>Gold falls more than 2% for the month, settles...</td>
      <td>Jun. 30, 2022 at 2:47 p.m. ET</td>
      <td>by Joseph Adinolfi</td>
    </tr>
    <tr>
      <th>1</th>
      <td>AMD stock gets an upgrade as analyst says rece...</td>
      <td>Jun. 30, 2022 at 12:07 p.m. ET</td>
      <td>by Emily Bary</td>
    </tr>
    <tr>
      <th>2</th>
      <td>All 30 Dow stocks are falling, with Goldman Sa...</td>
      <td>Jun. 30, 2022 at 9:47 a.m. ET</td>
      <td>by Tomi Kilgore</td>
    </tr>
    <tr>
      <th>3</th>
      <td>Here’s how far oil could fall in a recession, ...</td>
      <td>Jun. 30, 2022 at 8:34 a.m. ET</td>
      <td>by Steve Goldstein</td>
    </tr>
    <tr>
      <th>4</th>
      <td>Crypto Winter Is Coming After SEC Rejects Key ...</td>
      <td>Jun. 30, 2022 at 6:37 a.m. ET</td>
      <td></td>
    </tr>
    <tr>
      <th>5</th>
      <td>An FCC Commissioner Wants TikTok Yanked From A...</td>
      <td>Jun. 30, 2022 at 3:27 a.m. ET</td>
      <td>by Barron's</td>
    </tr>
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      <th>6</th>
      <td>Meta Has a New Problem. Profit Forecasts Now L...</td>
      <td>Jun. 29, 2022 at 1:18 p.m. ET</td>
      <td>by Barron's</td>
    </tr>
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      <th>7</th>
      <td>Fed rolls out new index to flag early warning ...</td>
      <td>Jun. 29, 2022 at 1:04 p.m. ET</td>
      <td>by Joy Wiltermuth</td>
    </tr>
    <tr>
      <th>8</th>
      <td>Apple Investors Have Something New to Focus On...</td>
      <td>Jun. 29, 2022 at 12:41 p.m. ET</td>
      <td>by Barron's</td>
    </tr>
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      <th>9</th>
      <td>Here’s why this trader is piling back into one...</td>
      <td>Jun. 29, 2022 at 10:34 a.m. ET</td>
      <td>by Barbara Kollmeyer</td>
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<h3 id="market-watch-streaming">Market Watch (Streaming)<a class="anchor-link" href="#market-watch-streaming">&#182;</a></h3>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="kn">from</span> <span class="nn">finnlp.data_sources.news.marketwatch_streaming</span> <span class="kn">import</span> <span class="n">MarketWatch_Streaming</span>
</pre></div>
<div id="cell-40" class="clipboard-copy-txt">from finnlp.data_sources.news.marketwatch_streaming import MarketWatch_Streaming</div>
        
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">news_downloader</span> <span class="o">=</span> <span class="n">MarketWatch_Streaming</span><span class="p">()</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">download_streaming_search</span><span class="p">(</span><span class="n">keyword</span> <span class="o">=</span> <span class="s2">&quot;apple&quot;</span><span class="p">,</span> <span class="n">rounds</span> <span class="o">=</span> <span class="mi">3</span><span class="p">)</span>
</pre></div>
<div id="cell-41" class="clipboard-copy-txt">news_downloader = MarketWatch_Streaming()
news_downloader.download_streaming_search(keyword = "apple", rounds = 3)</div>
        
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<pre>Only support the first page now!
</pre>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">selected_columns</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;title&quot;</span><span class="p">,</span> <span class="s2">&quot;time&quot;</span><span class="p">,</span> <span class="s2">&quot;author&quot;</span><span class="p">]</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">dataframe</span><span class="p">[</span><span class="n">selected_columns</span><span class="p">]</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
</pre></div>
<div id="cell-42" class="clipboard-copy-txt">selected_columns = ["title", "time", "author"]
news_downloader.dataframe[selected_columns].head(10)</div>
        
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    <tr>
      <th>0</th>
      <td>Tech IPOs Should Be Heating Up. Why They’re Not.</td>
      <td>Jun. 23, 2023 at 2:51 a.m. ET</td>
      <td>by Barron's</td>
    </tr>
    <tr>
      <th>1</th>
      <td>Everything Is Going Right for Tesla. It’s Time...</td>
      <td>Jun. 23, 2023 at 1:30 a.m. ET</td>
      <td>by Barron's</td>
    </tr>
    <tr>
      <th>2</th>
      <td>India’s Modi cracks jokes, chows down at swank...</td>
      <td>Jun. 22, 2023 at 11:38 p.m. ET</td>
      <td>by Associated Press</td>
    </tr>
    <tr>
      <th>3</th>
      <td>Work-From-Home Job Openings Are Shrinking</td>
      <td>Jun. 22, 2023 at 6:23 p.m. ET</td>
      <td>by Barron's</td>
    </tr>
    <tr>
      <th>4</th>
      <td>Congress Blasts E-Commerce Firm Temu Over Forc...</td>
      <td>Jun. 22, 2023 at 5:44 p.m. ET</td>
      <td>by Barron's</td>
    </tr>
    <tr>
      <th>5</th>
      <td>Meta Platforms Inc. stock outperforms market o...</td>
      <td>Jun. 22, 2023 at 5:32 p.m. ET</td>
      <td>by MarketWatch Automation</td>
    </tr>
    <tr>
      <th>6</th>
      <td>Microsoft Corp. stock outperforms competitors ...</td>
      <td>Jun. 22, 2023 at 5:32 p.m. ET</td>
      <td>by MarketWatch Automation</td>
    </tr>
    <tr>
      <th>7</th>
      <td>Netflix Inc. stock underperforms Thursday when...</td>
      <td>Jun. 22, 2023 at 5:32 p.m. ET</td>
      <td>by MarketWatch Automation</td>
    </tr>
    <tr>
      <th>8</th>
      <td>GameStop Corp. Cl A stock underperforms Thursd...</td>
      <td>Jun. 22, 2023 at 5:29 p.m. ET</td>
      <td>by MarketWatch Automation</td>
    </tr>
    <tr>
      <th>9</th>
      <td>Amazon.com Inc. stock outperforms market on st...</td>
      <td>Jun. 22, 2023 at 5:25 p.m. ET</td>
      <td>by MarketWatch Automation</td>
    </tr>
  </tbody>
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<h3 id="penny-stock">Penny Stock<a class="anchor-link" href="#penny-stock">&#182;</a></h3>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="kn">from</span> <span class="nn">finnlp.data_sources.news.pennystocks_streaming</span> <span class="kn">import</span> <span class="n">PennyStocks_Streaming</span>
</pre></div>
<div id="cell-43" class="clipboard-copy-txt">from finnlp.data_sources.news.pennystocks_streaming import PennyStocks_Streaming</div>
        
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">news_downloader</span> <span class="o">=</span> <span class="n">PennyStocks_Streaming</span><span class="p">()</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">download_streaming_search</span><span class="p">(</span><span class="n">keyword</span> <span class="o">=</span> <span class="s2">&quot;apple&quot;</span><span class="p">,</span> <span class="n">rounds</span> <span class="o">=</span> <span class="mi">3</span><span class="p">)</span>
</pre></div>
<div id="cell-44" class="clipboard-copy-txt">news_downloader = PennyStocks_Streaming()
news_downloader.download_streaming_search(keyword = "apple", rounds = 3)</div>
        
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<pre>Requesting https://pennystocks.com ... succeed!
Gathering again .. Remaining Retry: 4
Only support the first page now!
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">selected_columns</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;title&quot;</span><span class="p">,</span> <span class="s2">&quot;time&quot;</span><span class="p">,</span> <span class="s2">&quot;brief&quot;</span><span class="p">,</span> <span class="s2">&quot;reading_time&quot;</span><span class="p">]</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">dataframe</span><span class="p">[</span><span class="n">selected_columns</span><span class="p">]</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
</pre></div>
<div id="cell-45" class="clipboard-copy-txt">selected_columns = ["title", "time", "brief", "reading_time"]
news_downloader.dataframe[selected_columns].head(10)</div>
        
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      <th>0</th>
      <td>Best Penny Stocks to Buy Ahead Of Apple’s Even...</td>
      <td>September 14, 2021</td>
      <td>\r\n\r\n\t\t\t\r\n\t\t\tWhat do penny stock in...</td>
      <td>5 minute read</td>
    </tr>
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      <th>0</th>
      <td>What Could The Apple Event Mean For Penny Stoc...</td>
      <td>October 13, 2020</td>
      <td>\r\n\r\n\t\t\t\r\n\t\t\tWill The Apple Event M...</td>
      <td>5 minute read</td>
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      <th>0</th>
      <td>3 Red Hot Penny Stocks To Watch Before Next We...</td>
      <td>June 14, 2023</td>
      <td>\r\n\r\n\t\t\t\r\n\t\t\tPenny stocks to watch.\n</td>
      <td>4 minute read</td>
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      <th>0</th>
      <td>Penny Stocks Definition &amp; 7 Trading Strategies...</td>
      <td>June 8, 2023</td>
      <td>\r\n\r\n\t\t\t\r\n\t\t\tWhat Is A Penny Stock?...</td>
      <td>6 minute read</td>
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      <td>Best Penny Stocks To Buy? 5 With Big News This...</td>
      <td>June 7, 2023</td>
      <td>\r\n\r\n\t\t\t\r\n\t\t\tPenny stocks to watch ...</td>
      <td>4 minute read</td>
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      <td>Penny Stocks &amp; The Stock Market Today: Top Tre...</td>
      <td>May 30, 2023</td>
      <td>\r\n\r\n\t\t\t\r\n\t\t\tWhat happened in the s...</td>
      <td>6 minute read</td>
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      <th>0</th>
      <td>Penny Stocks To Buy? 3 AI Stocks To Watch Righ...</td>
      <td>May 30, 2023</td>
      <td>\r\n\r\n\t\t\t\r\n\t\t\tAI penny stocks to wat...</td>
      <td>5 minute read</td>
    </tr>
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      <th>0</th>
      <td>What Are Penny Stocks &amp; Should You Buy Them In...</td>
      <td>May 19, 2023</td>
      <td>\r\n\r\n\t\t\t\r\n\t\t\tShould You Find Penny ...</td>
      <td>6 minute read</td>
    </tr>
    <tr>
      <th>0</th>
      <td>Trading Penny Stocks: 3 High-Growth Industries...</td>
      <td>May 8, 2023</td>
      <td>\r\n\r\n\t\t\t\r\n\t\t\tWatch these three indu...</td>
      <td>7 minute read</td>
    </tr>
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      <th>0</th>
      <td>Fed Meeting Live Updates: 10 Takeaways From Ma...</td>
      <td>May 3, 2023</td>
      <td>\r\n\r\n\t\t\t\r\n\t\t\tFOMC Statement From Ma...</td>
      <td>10 minute read</td>
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<h3 id="seeking-alpha">Seeking Alpha<a class="anchor-link" href="#seeking-alpha">&#182;</a></h3>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="kn">from</span> <span class="nn">finnlp.data_sources.news.seekingalpha_date_range</span> <span class="kn">import</span> <span class="n">SeekingAlpha_Date_Range</span>
</pre></div>
<div id="cell-46" class="clipboard-copy-txt">from finnlp.data_sources.news.seekingalpha_date_range import SeekingAlpha_Date_Range</div>
        
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">start_date</span> <span class="o">=</span> <span class="s2">&quot;2023-06-01&quot;</span>
<span class="n">end_date</span> <span class="o">=</span> <span class="s2">&quot;2023-06-30&quot;</span>
<span class="n">stock</span> <span class="o">=</span> <span class="s2">&quot;AAPL&quot;</span>
</pre></div>
<div id="cell-47" class="clipboard-copy-txt">start_date = "2023-06-01"
end_date = "2023-06-30"
stock = "AAPL"</div>
        
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">news_downloader</span> <span class="o">=</span> <span class="n">SeekingAlpha_Date_Range</span><span class="p">()</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">download_date_range_stock</span><span class="p">(</span><span class="n">start_date</span><span class="p">,</span> <span class="n">end_date</span><span class="p">,</span> <span class="n">stock</span><span class="p">)</span>
</pre></div>
<div id="cell-48" class="clipboard-copy-txt">news_downloader = SeekingAlpha_Date_Range()
news_downloader.download_date_range_stock(start_date, end_date, stock)</div>
        
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<pre>Downloading Titles: 100%|██████████| 1/1 [00:00&lt;?, ?it/s]
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">selected_columns</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;publishOn&quot;</span><span class="p">,</span><span class="s2">&quot;title&quot;</span><span class="p">,</span><span class="s2">&quot;commentCount&quot;</span><span class="p">]</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">dataframe</span><span class="p">[</span><span class="n">selected_columns</span><span class="p">]</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
</pre></div>
<div id="cell-49" class="clipboard-copy-txt">selected_columns = ["publishOn","title","commentCount"]
news_downloader.dataframe[selected_columns].head(10)</div>
        
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  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>2023-06-19T09:00:00-04:00</td>
      <td>Artificial intelligence is a '1995 moment' for...</td>
      <td>63</td>
    </tr>
    <tr>
      <th>1</th>
      <td>2023-06-16T11:59:46-04:00</td>
      <td>Citi: Don't worry about Big Tech fueling 2023'...</td>
      <td>17</td>
    </tr>
    <tr>
      <th>2</th>
      <td>2023-06-15T07:20:12-04:00</td>
      <td>Google said to temper chatbot use for employee...</td>
      <td>8</td>
    </tr>
    <tr>
      <th>3</th>
      <td>2023-06-14T05:17:31-04:00</td>
      <td>Nvidia crosses $1T market cap powered by the r...</td>
      <td>36</td>
    </tr>
    <tr>
      <th>4</th>
      <td>2023-06-13T17:17:00-04:00</td>
      <td>Intel in talks to be anchor investor in chip d...</td>
      <td>94</td>
    </tr>
    <tr>
      <th>5</th>
      <td>2023-06-13T12:14:45-04:00</td>
      <td>Hot Stocks: AAPL falls on downgrade; MANU rise...</td>
      <td>3</td>
    </tr>
    <tr>
      <th>6</th>
      <td>2023-06-13T06:22:59-04:00</td>
      <td>Apple notches record close as bulls continue t...</td>
      <td>18</td>
    </tr>
    <tr>
      <th>7</th>
      <td>2023-06-13T04:49:26-04:00</td>
      <td>Apple cut to Neutral at UBS on softer iPhone a...</td>
      <td>26</td>
    </tr>
    <tr>
      <th>8</th>
      <td>2023-06-09T05:42:17-04:00</td>
      <td>AI looking like a 'winner-take-more' game - Go...</td>
      <td>39</td>
    </tr>
    <tr>
      <th>9</th>
      <td>2023-06-09T05:21:04-04:00</td>
      <td>Zuckerberg's vision for AR/VR headsets differe...</td>
      <td>92</td>
    </tr>
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</table>
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<h3 id="reuters">Reuters<a class="anchor-link" href="#reuters">&#182;</a></h3>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="kn">from</span> <span class="nn">finnlp.data_sources.news.reuters_streaming</span> <span class="kn">import</span> <span class="n">Reuters_Streaming</span>
</pre></div>
<div id="cell-50" class="clipboard-copy-txt">from finnlp.data_sources.news.reuters_streaming import Reuters_Streaming</div>
        
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">news_downloader</span> <span class="o">=</span> <span class="n">Reuters_Streaming</span><span class="p">()</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">download_streaming_search</span><span class="p">(</span><span class="n">keyword</span> <span class="o">=</span> <span class="s2">&quot;apple&quot;</span><span class="p">,</span> <span class="n">rounds</span> <span class="o">=</span> <span class="mi">3</span><span class="p">)</span>
</pre></div>
<div id="cell-51" class="clipboard-copy-txt">news_downloader = Reuters_Streaming()
news_downloader.download_streaming_search(keyword = "apple", rounds = 3)</div>
        
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<pre>Geting pages: 1 2 3 </pre>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">selected_columns</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;published_time&quot;</span><span class="p">,</span><span class="s2">&quot;title&quot;</span><span class="p">,</span><span class="s2">&quot;description&quot;</span><span class="p">]</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">dataframe</span><span class="p">[</span><span class="n">selected_columns</span><span class="p">]</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
</pre></div>
<div id="cell-52" class="clipboard-copy-txt">selected_columns = ["published_time","title","description"]
news_downloader.dataframe[selected_columns].head(10)</div>
        
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    .dataframe tbody tr th:only-of-type {
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        text-align: right;
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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>published_time</th>
      <th>title</th>
      <th>description</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>2023-06-19T10:17:24.474Z</td>
      <td>Hong Kong tycoon Jimmy Lai loses appeal agains...</td>
      <td>A Hong Kong appeal court on Monday blocked jai...</td>
    </tr>
    <tr>
      <th>1</th>
      <td>2023-06-19T09:49:09.391Z</td>
      <td>Podcast: Blinken meets Xi and Chinese bankers ...</td>
      <td>U.S. Secretary of State Anthony Blinken is in ...</td>
    </tr>
    <tr>
      <th>2</th>
      <td>2023-06-19T02:10:24.581Z</td>
      <td>Their parents made China the world's factory. ...</td>
      <td>When Steven Du took over his parents' factory ...</td>
    </tr>
    <tr>
      <th>3</th>
      <td>2023-06-17T08:14:15.708Z</td>
      <td>Japan to open up Apple- and Google-dominated p...</td>
      <td>Japan plans to stoke competition in smartphone...</td>
    </tr>
    <tr>
      <th>4</th>
      <td>2023-06-16T13:28:02.538Z</td>
      <td>Khashoggi's widow sues Israeli spyware company...</td>
      <td>The widow of murdered Saudi journalist Jamal K...</td>
    </tr>
    <tr>
      <th>5</th>
      <td>2023-06-16T11:12:02.899Z</td>
      <td>Factbox: DLE companies racing to reshape globa...</td>
      <td>Lithium, the metal used to make electric vehic...</td>
    </tr>
    <tr>
      <th>6</th>
      <td>2023-06-16T10:17:23.831Z</td>
      <td>Podcast: US-Iran talks and Australia divided o...</td>
      <td>Australia is divided on a historic referendum ...</td>
    </tr>
    <tr>
      <th>7</th>
      <td>2023-06-16T02:16:44.523Z</td>
      <td>Chinese e-commerce giants entice cautious cons...</td>
      <td>China's e-commerce platforms are competing fie...</td>
    </tr>
    <tr>
      <th>8</th>
      <td>2023-06-15T10:21:02.697Z</td>
      <td>S&amp;P 500 leaps to highest close in 14 months; t...</td>
      <td>The S&amp;P 500 and Nasdaq surged on Thursday to c...</td>
    </tr>
    <tr>
      <th>9</th>
      <td>2023-06-15T19:49:27.459Z</td>
      <td>Microsoft notches record high valuation of nea...</td>
      <td>Microsoft Corp shares rose to a new record hig...</td>
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<h3 id="sina-finance">Sina Finance<a class="anchor-link" href="#sina-finance">&#182;</a></h3>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="kn">from</span> <span class="nn">finnlp.data_sources.news.sina_finance_date_range</span> <span class="kn">import</span> <span class="n">Sina_Finance_Date_Range</span>
</pre></div>
<div id="cell-53" class="clipboard-copy-txt">from finnlp.data_sources.news.sina_finance_date_range import Sina_Finance_Date_Range</div>
        
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">start_date</span> <span class="o">=</span> <span class="s2">&quot;2016-01-01&quot;</span>
<span class="n">end_date</span> <span class="o">=</span> <span class="s2">&quot;2016-01-01&quot;</span>
<span class="n">config</span> <span class="o">=</span> <span class="p">{</span>
    <span class="s2">&quot;use_proxy&quot;</span><span class="p">:</span> <span class="s2">&quot;china_free&quot;</span><span class="p">,</span>
    <span class="s2">&quot;max_retry&quot;</span><span class="p">:</span> <span class="mi">5</span><span class="p">,</span>
    <span class="s2">&quot;proxy_pages&quot;</span><span class="p">:</span> <span class="mi">5</span><span class="p">,</span>
<span class="p">}</span>
</pre></div>
<div id="cell-54" class="clipboard-copy-txt">start_date = "2016-01-01"
end_date = "2016-01-01"
config = {
    "use_proxy": "china_free",
    "max_retry": 5,
    "proxy_pages": 5,
}</div>
        
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">news_downloader</span> <span class="o">=</span> <span class="n">Sina_Finance_Date_Range</span><span class="p">(</span><span class="n">config</span><span class="p">)</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">download_date_range_all</span><span class="p">(</span><span class="n">start_date</span><span class="p">,</span><span class="n">end_date</span><span class="p">)</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">gather_content</span><span class="p">()</span>
</pre></div>
<div id="cell-55" class="clipboard-copy-txt">news_downloader = Sina_Finance_Date_Range(config)
news_downloader.download_date_range_all(start_date,end_date)
news_downloader.gather_content()</div>
        
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<pre>Gathering free ips by pages...: 100%|██████████| 5/5 [00:04&lt;00:00,  1.05it/s]
Checking ips: 100%|██████████| 75/75 [00:20&lt;00:00,  3.67it/s]
</pre>
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<pre>获取到的代理ip数量: 75 。Get proxy ips: 75.
能用的代理数量： 75。Usable proxy ips: 75.
</pre>
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<pre>Downloading Titles...: 100%|██████████| 1/1 [00:01&lt;00:00,  1.54s/it]
Gathering news contents: 100%|██████████| 103/103 [00:22&lt;00:00,  4.50it/s]
</pre>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">selected_columns</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;title&quot;</span><span class="p">,</span> <span class="s2">&quot;content&quot;</span><span class="p">]</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">dataframe</span><span class="p">[</span><span class="n">selected_columns</span><span class="p">]</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
</pre></div>
<div id="cell-56" class="clipboard-copy-txt">selected_columns = ["title", "content"]
news_downloader.dataframe[selected_columns].head(10)</div>
        
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      <th>content</th>
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      <th>0</th>
      <td>分析师：伊朗重回国际原油市场无法阻止</td>
      <td>新浪美股讯 北京时间1月1日晚CNBC称，加拿大皇家银行（RBC）分析师Helima Cro...</td>
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      <th>1</th>
      <td>FAA：波音767的逃生扶梯存在缺陷</td>
      <td>新浪美股讯 北京时间1日晚，美国联邦航空局（FAA）要求航空公司对波音767机型的救生扶梯进...</td>
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    <tr>
      <th>2</th>
      <td>非制造业新订单指数创新高 需求回升力度明显</td>
      <td>中新社北京1月1日电 （记者 刘长忠）记者1日从中国物流与采购联合会获悉，在最新发布的201...</td>
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    <tr>
      <th>3</th>
      <td>雷曼兄弟针对大和证券提起索赔诉讼</td>
      <td>新浪美股讯 北京时间1日下午共同社称，2008年破产的美国金融巨头雷曼兄弟公司的清算法人日前...</td>
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      <th>4</th>
      <td>国内钢铁PMI有所回升 钢市低迷形势有所改善</td>
      <td>新华社上海1月1日专电（记者李荣）据中物联钢铁物流专业委员会1日发布的指数报告，2015年1...</td>
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      <th>5</th>
      <td>马息岭凸显朝鲜旅游体育战略</td>
      <td>新浪美股北京时间1日讯 三位单板滑雪手将成为最早拜访马息岭滑雪场的西方专业运动员，他们本月就...</td>
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      <th>6</th>
      <td>五洲船舶破产清算 近十年来首现国有船厂倒闭</td>
      <td>（原标题：中国首家国有船厂破产倒闭）\n低迷的中国造船市场，多年来首次出现国有船厂破产清算的...</td>
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      <th>7</th>
      <td>过半城市房价环比上涨 百城住宅均价加速升温</td>
      <td>资料图。中新社记者 武俊杰 摄\n中新社北京1月1日电 (记者 庞无忌)中国房地产市场在20...</td>
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      <th>8</th>
      <td>经济学人：巴西病根到底在哪里</td>
      <td>新浪美股北京时间1日讯 原本，巴西人是该高高兴兴迎接2016年的。8月间，里约热内卢将举办南...</td>
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    <tr>
      <th>9</th>
      <td>中国首家国有船厂破产倒闭:五洲船舶目前已停工</td>
      <td>低迷的中国造船市场，多年来首次出现国有船厂破产清算的一幕。浙江海运集团旗下的五洲船舶修造公司...</td>
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</table>
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<h3 id="eastmoney">Eastmoney<a class="anchor-link" href="#eastmoney">&#182;</a></h3>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="kn">from</span> <span class="nn">finnlp.data_sources.news.eastmoney_streaming</span> <span class="kn">import</span> <span class="n">Eastmoney_Streaming</span>
</pre></div>
<div id="cell-57" class="clipboard-copy-txt">from finnlp.data_sources.news.eastmoney_streaming import Eastmoney_Streaming</div>
        
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">pages</span> <span class="o">=</span> <span class="mi">3</span>
<span class="n">stock</span> <span class="o">=</span> <span class="s2">&quot;600519&quot;</span>
<span class="n">config</span> <span class="o">=</span> <span class="p">{</span>
    <span class="s2">&quot;use_proxy&quot;</span><span class="p">:</span> <span class="s2">&quot;china_free&quot;</span><span class="p">,</span>
    <span class="s2">&quot;max_retry&quot;</span><span class="p">:</span> <span class="mi">5</span><span class="p">,</span>
    <span class="s2">&quot;proxy_pages&quot;</span><span class="p">:</span> <span class="mi">5</span><span class="p">,</span>
<span class="p">}</span>
</pre></div>
<div id="cell-58" class="clipboard-copy-txt">pages = 3
stock = "600519"
config = {
    "use_proxy": "china_free",
    "max_retry": 5,
    "proxy_pages": 5,
}</div>
        
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">news_downloader</span> <span class="o">=</span> <span class="n">Eastmoney_Streaming</span><span class="p">(</span><span class="n">config</span><span class="p">)</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">download_streaming_stock</span><span class="p">(</span><span class="n">stock</span><span class="p">,</span><span class="n">pages</span><span class="p">)</span>
</pre></div>
<div id="cell-59" class="clipboard-copy-txt">news_downloader = Eastmoney_Streaming(config)
news_downloader.download_streaming_stock(stock,pages)</div>
        
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<pre>Gathering free ips by pages...: 100%|██████████| 5/5 [00:04&lt;00:00,  1.08it/s]
Checking ips: 100%|██████████| 75/75 [00:20&lt;00:00,  3.62it/s]
</pre>
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<pre>获取到的代理ip数量: 75 。Get proxy ips: 75.
能用的代理数量： 75。Usable proxy ips: 75.
Geting pages: 0 1 2 Get total 3 pages.
</pre>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">selected_columns</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;title&quot;</span><span class="p">,</span> <span class="s2">&quot;create time&quot;</span><span class="p">]</span>
<span class="n">news_downloader</span><span class="p">[</span><span class="n">selected_columns</span><span class="p">]</span><span class="o">.</span><span class="n">dataframe</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
</pre></div>
<div id="cell-60" class="clipboard-copy-txt">selected_columns = ["title", "create time"]
news_downloader[selected_columns].dataframe.head(10)</div>
        
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      <td>6</td>
      <td>茅台2022年报的12个小秘密</td>
      <td>/news,600519,1295554981.html</td>
      <td>贵州茅台资讯</td>
      <td>04-09 19:40</td>
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      <td>公司研报提示</td>
      <td>04-09 11:24</td>
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      <td>贵州茅台：融资余额169.34亿元，创近一年新低（04-07</td>
      <td>/news,600519,1295407809.html</td>
      <td>贵州茅台资讯</td>
      <td>04-08 07:30</td>
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      <td>233</td>
      <td>0</td>
      <td>贵州茅台：融资净买入1248.48万元，融资余额169.79亿</td>
      <td>/news,600519,1294929438.html</td>
      <td>贵州茅台资讯</td>
      <td>04-07 07:28</td>
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      <td>贵州茅台公益基金会正式成立</td>
      <td>/news,600519,1294612056.html</td>
      <td>贵州茅台资讯</td>
      <td>04-06 12:29</td>
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    <tr>
      <th>5</th>
      <td>333</td>
      <td>0</td>
      <td>贵州茅台04月04日获沪股通增持19.55万股</td>
      <td>/news,600519,1294268016.html</td>
      <td>贵州茅台资讯</td>
      <td>04-05 07:48</td>
    </tr>
    <tr>
      <th>6</th>
      <td>312</td>
      <td>0</td>
      <td>贵州茅台：融资余额169.66亿元，创近一年新低（04-04</td>
      <td>/news,600519,1294265710.html</td>
      <td>贵州茅台资讯</td>
      <td>04-05 07:30</td>
    </tr>
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      <th>7</th>
      <td>22721</td>
      <td>16</td>
      <td>4月4日北向资金最新动向（附十大成交股）</td>
      <td>/news,600519,1294192188.html</td>
      <td>贵州茅台资讯</td>
      <td>04-04 18:48</td>
    </tr>
    <tr>
      <th>8</th>
      <td>654</td>
      <td>1</td>
      <td>大宗交易：贵州茅台成交235.9万元，成交价1814.59元（</td>
      <td>/news,600519,1294173281.html</td>
      <td>贵州茅台资讯</td>
      <td>04-04 17:21</td>
    </tr>
    <tr>
      <th>9</th>
      <td>233</td>
      <td>0</td>
      <td>第一上海证券维持贵州茅台买入评级 目标价2428.8元</td>
      <td>/news,600519,1293784734.html</td>
      <td>公司研报提示</td>
      <td>04-04 09:30</td>
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<h3 id="finnhub-yahoo">Finnhub / Yahoo<a class="anchor-link" href="#finnhub-yahoo">&#182;</a></h3>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="kn">from</span> <span class="nn">finnlp.data_sources.news.finnhub_date_range</span> <span class="kn">import</span> <span class="n">Finnhub_Date_Range</span>
</pre></div>
<div id="cell-61" class="clipboard-copy-txt">from finnlp.data_sources.news.finnhub_date_range import Finnhub_Date_Range</div>
        
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">start_date</span> <span class="o">=</span> <span class="s2">&quot;2023-01-01&quot;</span>
<span class="n">end_date</span> <span class="o">=</span> <span class="s2">&quot;2023-01-03&quot;</span>
<span class="n">config</span> <span class="o">=</span> <span class="p">{</span>
    <span class="s2">&quot;use_proxy&quot;</span><span class="p">:</span> <span class="s2">&quot;us_free&quot;</span><span class="p">,</span>
    <span class="s2">&quot;max_retry&quot;</span><span class="p">:</span> <span class="mi">5</span><span class="p">,</span>
    <span class="s2">&quot;proxy_pages&quot;</span><span class="p">:</span> <span class="mi">5</span><span class="p">,</span>
    <span class="s2">&quot;token&quot;</span><span class="p">:</span> <span class="s2">&quot;YOUR_FINNHUB_TOKEN&quot;</span>  <span class="c1"># Avaliable at https://finnhub.io/dashboard</span>
<span class="p">}</span>
</pre></div>
<div id="cell-62" class="clipboard-copy-txt">start_date = "2023-01-01"
end_date = "2023-01-03"
config = {
    "use_proxy": "us_free",
    "max_retry": 5,
    "proxy_pages": 5,
    "token": "YOUR_FINNHUB_TOKEN"  # Avaliable at https://finnhub.io/dashboard
}</div>
        
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">news_downloader</span> <span class="o">=</span> <span class="n">Finnhub_Date_Range</span><span class="p">(</span><span class="n">config</span><span class="p">)</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">download_date_range_stock</span><span class="p">(</span><span class="n">start_date</span><span class="p">,</span><span class="n">end_date</span><span class="p">)</span>
<span class="n">news_downloader</span><span class="o">.</span><span class="n">gather_content</span><span class="p">()</span>
</pre></div>
<div id="cell-63" class="clipboard-copy-txt">news_downloader = Finnhub_Date_Range(config)
news_downloader.download_date_range_stock(start_date,end_date)
news_downloader.gather_content()</div>
        
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<pre>Checking ips: 100%|██████████| 75/75 [02:51&lt;00:00,  2.28s/it]
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<pre>Get proxy ips: 75.
Usable proxy ips: 75.
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<pre>Downloading Titles: 100%|██████████| 1/1 [00:02&lt;00:00,  2.66s/it]
Gathering news contents:  48%|████▊     | 49/102 [03:18&lt;02:51,  3.24s/it]c:\Users\Olive\.conda\envs\finrl\lib\site-packages\urllib3\connectionpool.py:1052: InsecureRequestWarning: Unverified HTTPS request is being made to host &#39;thefly.com&#39;. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/1.26.x/advanced-usage.html#ssl-warnings
  InsecureRequestWarning,
Gathering news contents: 100%|██████████| 102/102 [06:15&lt;00:00,  3.68s/it]
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">df</span> <span class="o">=</span> <span class="n">news_downloader</span><span class="o">.</span><span class="n">dataframe</span>
<span class="n">df</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span>
</pre></div>
<div id="cell-64" class="clipboard-copy-txt">df = news_downloader.dataframe
df.head(2)</div>
        
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        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>category</th>
      <th>datetime</th>
      <th>headline</th>
      <th>id</th>
      <th>image</th>
      <th>related</th>
      <th>source</th>
      <th>summary</th>
      <th>url</th>
      <th>content</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>company</td>
      <td>2023-01-03 23:40:08</td>
      <td>My 26-Stock $349k Portfolio Gets A Nice Petrob...</td>
      <td>118107004</td>
      <td>https://media.gettyimages.com/id/1441204186/ph...</td>
      <td>AAPL</td>
      <td>SeekingAlpha</td>
      <td>My portfolio, built specifically for my retire...</td>
      <td>https://finnhub.io/api/news?id=d3c15f6f365663b...</td>
      <td>Home\nInvesting Strategy\nPortfolio Strategy\n...</td>
    </tr>
    <tr>
      <th>1</th>
      <td>company</td>
      <td>2023-01-03 22:09:00</td>
      <td>Apple’s Market Cap Slides Below $2 Trillion fo...</td>
      <td>118105849</td>
      <td></td>
      <td>AAPL</td>
      <td>Yahoo</td>
      <td>The tech giant is one of only five U.S. compan...</td>
      <td>https://finnhub.io/api/news?id=42343678a7474e1...</td>
      <td>Error</td>
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            <div class="highlight-ipynb hl-python "><pre><span></span><span class="n">selected_columns</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;headline&quot;</span><span class="p">,</span> <span class="s2">&quot;content&quot;</span><span class="p">]</span>
<span class="n">df</span><span class="p">[</span><span class="n">selected_columns</span><span class="p">]</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
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<div id="cell-65" class="clipboard-copy-txt">selected_columns = ["headline", "content"]
df[selected_columns].head(10)</div>
        
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      <td>My 26-Stock $349k Portfolio Gets A Nice Petrob...</td>
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      <th>1</th>
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      <td>Jan 3 (Reuters) - Apple Inc's \n(AAPL.O)\n sto...</td>
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      <td>CORRECTED-UPDATE 1-Apple's stock market value ...</td>
      <td>Jan 3 (Reuters) - Apple Inc's \n(AAPL.O)\n sto...</td>
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      <th>7</th>
      <td>US STOCKS-Wall St starts the year with a dip; ...</td>
      <td>Summary\nCompanies\nTesla shares plunge on Q4 ...</td>
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      <th>8</th>
      <td>More than $1 trillion wiped off value of Apple...</td>
      <td>apple store\nMore than $1 trillion has been wi...</td>
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      <th>9</th>
      <td>McLean's Iridium inks agreement to put its sat...</td>
      <td>The company hasn't named its partner, but it's...</td>
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